Back to Multiple platform build/check report for BioC 3.20: simplified long |
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This page was generated on 2024-12-23 12:07 -0500 (Mon, 23 Dec 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4744 |
palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" | 4487 |
merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4515 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4467 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
Package 1378/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
MungeSumstats 1.14.1 (landing page) Alan Murphy
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | TIMEOUT | OK | |||||||||
kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | OK | |||||||||
To the developers/maintainers of the MungeSumstats package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/MungeSumstats.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: MungeSumstats |
Version: 1.14.1 |
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:MungeSumstats.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings MungeSumstats_1.14.1.tar.gz |
StartedAt: 2024-12-21 02:50:18 -0500 (Sat, 21 Dec 2024) |
EndedAt: 2024-12-21 03:07:09 -0500 (Sat, 21 Dec 2024) |
EllapsedTime: 1010.4 seconds |
RetCode: 0 |
Status: OK |
CheckDir: MungeSumstats.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:MungeSumstats.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings MungeSumstats_1.14.1.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/MungeSumstats.Rcheck’ * using R version 4.4.2 (2024-10-31) * using platform: aarch64-apple-darwin20 * R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 12.2.0 * running under: macOS Ventura 13.7.1 * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘MungeSumstats/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘MungeSumstats’ version ‘1.14.1’ * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... NOTE Found the following hidden files and directories: .BBSoptions These were most likely included in error. See section ‘Package structure’ in the ‘Writing R Extensions’ manual. * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘MungeSumstats’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking whether startup messages can be suppressed ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... NOTE checkRd: (-1) check_no_chr_bp.Rd:56-57: Lost braces 56 | \item \code{sumstats_dt}{ | ^ checkRd: (-1) check_no_chr_bp.Rd:58-59: Lost braces 58 | \item \code{rsids}{ | ^ checkRd: (-1) check_no_chr_bp.Rd:60-61: Lost braces 60 | \item \code{log_files}{ | ^ checkRd: (-1) check_on_ref_genome.Rd:65-66: Lost braces 65 | \item \code{sumstats_dt}{ | ^ checkRd: (-1) check_on_ref_genome.Rd:67-68: Lost braces 67 | \item \code{rsids}{ | ^ checkRd: (-1) check_on_ref_genome.Rd:69-70: Lost braces 69 | \item \code{log_files}{ | ^ checkRd: (-1) compute_nsize.Rd:32: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_nsize.Rd:33-36: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_nsize.Rd:37-38: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_nsize.Rd:39-40: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_nsize.Rd:41-42: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_nsize.Rd:43-44: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size.Rd:21-28: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size.Rd:30-34: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size.Rd:36-40: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size.Rd:42-46: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size.Rd:48-52: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_n.Rd:16-23: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_n.Rd:25-29: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_n.Rd:31-35: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_n.Rd:37-41: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_n.Rd:43-47: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_neff.Rd:21-28: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_neff.Rd:30-34: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_neff.Rd:36-40: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_neff.Rd:42-46: Lost braces in \itemize; meant \describe ? checkRd: (-1) compute_sample_size_neff.Rd:48-52: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_sumstats.Rd:29: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_sumstats.Rd:30: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_sumstats.Rd:31-32: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_vcf.Rd:64: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_vcf.Rd:65: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_vcf.Rd:66-67: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_vcf_parallel.Rd:40: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_vcf_parallel.Rd:41: Lost braces in \itemize; meant \describe ? checkRd: (-1) read_vcf_parallel.Rd:42-43: Lost braces in \itemize; meant \describe ? checkRd: (-1) select_vcf_fields.Rd:27: Lost braces in \itemize; meant \describe ? checkRd: (-1) select_vcf_fields.Rd:28: Lost braces in \itemize; meant \describe ? checkRd: (-1) select_vcf_fields.Rd:29-30: Lost braces in \itemize; meant \describe ? checkRd: (-1) sort_coords.Rd:19-21: Lost braces in \itemize; meant \describe ? checkRd: (-1) sort_coords.Rd:22-24: Lost braces in \itemize; meant \describe ? * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... OK * checking data for ASCII and uncompressed saves ... OK * checking R/sysdata.rda ... OK * checking files in ‘vignettes’ ... OK * checking examples ... OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed get_genome_builds 82.730 3.808 87.268 format_sumstats 68.927 3.167 73.239 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘testthat.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking running R code from vignettes ... SKIPPED * checking re-building of vignette outputs ... SKIPPED * checking PDF version of manual ... OK * DONE Status: 2 NOTEs See ‘/Users/biocbuild/bbs-3.20-bioc/meat/MungeSumstats.Rcheck/00check.log’ for details.
MungeSumstats.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL MungeSumstats ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library’ * installing *source* package ‘MungeSumstats’ ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (MungeSumstats)
MungeSumstats.Rcheck/tests/testthat.Rout
R version 4.4.2 (2024-10-31) -- "Pile of Leaves" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: aarch64-apple-darwin20 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(testthat) > library(MungeSumstats) > > test_check("MungeSumstats") ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988750895bf.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398816295ace Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A0 A1 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A0 A1 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988750895bf.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.081 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887cdaa386.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398816295ace Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887cdaa386.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.055 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39886035c1d7.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39885c821513 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Checking for bi-allelic SNPs. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 93 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 43 seconds. 1 SNPs are non-biallelic. These will be removed. Writing in tabular format ==> /tmp/RtmpfQlZhL/snp_bi_allelic.tsv.gz 46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39886035c1d7.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.79 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39883d0b5244.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39885c821513 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Checking for bi-allelic SNPs. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 93 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 20 seconds. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39883d0b5244.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.42 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Sorting coordinates with 'data.table'. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988124f8d7e.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Found 1 Indels. These will be removed from the sumstats. WARNING If you want to keep Indels, set the drop_indel param to FALSE & rerun MungeSumstats::format_sumstats() Writing in tabular format ==> /tmp/RtmpfQlZhL/indel.tsv.gz Loading required namespace: GenomicFiles Using local VCF. bgzip-compressing VCF file. Finding empty VCF columns based on first 10,000 rows. Dropping 1 duplicate column(s). 1 sample detected: EBI-a-GCST005647 Constructing ScanVcfParam object. VCF contains: 39,630,630 variant(s) x 1 sample(s) Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Dropping 1 duplicate column(s). Checking for empty columns. Unlisting 3 columns. Dropped 314 duplicate rows. Time difference of 0.1 secs VCF data.table contains: 101 rows x 11 columns. Time difference of 0.6 secs Renaming ID as SNP. sumstats has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. No INFO (SI) column detected. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988690c07d5.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39884bedcc7c Checking for empty columns. sumstats has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. Infer Effect Column First line of summary statistics file: SNP chr BP end REF ALT FILTER AF ES LP SE P N Standardising column headers. First line of summary statistics file: SNP chr BP end REF ALT FILTER AF ES LP SE P N Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988690c07d5.tsv.gz Summary statistics report: - 101 rows (100% of original 101 rows) - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Done munging in 0.052 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 END FILTER FRQ BETA LP <char> <int> <int> <char> <char> <int> <char> <num> <num> <num> 1: rs58108140 1 10583 G A 10583 PASS 0.1589 0.0312 0.369267 2: rs806731 1 30923 G T 30923 PASS 0.7843 -0.0114 0.126854 3: rs116400033 1 51479 T A 51479 PASS 0.1829 0.0711 1.262410 4: rs146477069 1 54421 A G 54421 PASS 0.0352 -0.0240 0.112102 SE P N <num> <num> <int> 1: 0.0393 0.42730011 293723 2: 0.0353 0.74669974 293723 3: 0.0370 0.05464998 293723 4: 0.0830 0.77249913 293723 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887898e1c8.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL sumstats has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. Infer Effect Column First line of summary statistics file: SNP chr BP end REF ALT FILTER AF ES LP SE P N Beta Standardising column headers. First line of summary statistics file: SNP chr BP end REF ALT FILTER AF ES LP SE P N Beta Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887898e1c8.tsv.gz Summary statistics report: - 101 rows (100% of original 101 rows) - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Done munging in 0.058 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 END FILTER FRQ ES LP <char> <int> <int> <char> <char> <int> <char> <num> <num> <num> 1: rs58108140 1 10583 G A 10583 PASS 0.1589 0.0312 0.369267 2: rs806731 1 30923 G T 30923 PASS 0.7843 -0.0114 0.126854 3: rs116400033 1 51479 T A 51479 PASS 0.1829 0.0711 1.262410 4: rs146477069 1 54421 A G 54421 PASS 0.0352 -0.0240 0.112102 SE P N BETA <num> <num> <int> <num> 1: 0.0393 0.42730011 293723 0.0312 2: 0.0353 0.74669974 293723 -0.0114 3: 0.0370 0.05464998 293723 0.0711 4: 0.0830 0.77249913 293723 -0.0240 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39881668f11.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39884bedcc7c Checking for empty columns. sumstats has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. Infer Effect Column First line of summary statistics file: SNP chr BP end REF ALT FILTER AF ES LP P N Standardising column headers. First line of summary statistics file: SNP chr BP end REF ALT FILTER AF ES LP P N Summary statistics report: - 101 rows - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. The sumstats SE column is not present...Deriving SE from Beta and P Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39881668f11.tsv.gz Summary statistics report: - 101 rows (100% of original 101 rows) - 101 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Done munging in 0.076 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 END FILTER FRQ BETA LP <char> <int> <int> <char> <char> <int> <char> <num> <num> <num> 1: rs58108140 1 10583 G A 10583 PASS 0.1589 0.0312 0.369267 2: rs806731 1 30923 G T 30923 PASS 0.7843 -0.0114 0.126854 3: rs116400033 1 51479 T A 51479 PASS 0.1829 0.0711 1.262410 4: rs146477069 1 54421 A G 54421 PASS 0.0352 -0.0240 0.112102 P N SE IMPUTATION_SE <num> <int> <num> <lgcl> 1: 0.42730011 293723 0.03930361 TRUE 2: 0.74669974 293723 0.03529477 TRUE 3: 0.05464998 293723 0.03699948 TRUE 4: 0.77249913 293723 0.08301411 TRUE Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887e7c627d.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39884bedcc7c Checking for empty columns. Infer Effect Column First line of summary statistics file: SNP CHR BP A1 A2 FRQ Z SE P N Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: SNP CHR BP A1 A2 FRQ Z SE P N Summary statistics report: - 25 rows - 25 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions The sumstats BETA column is not present...Deriving BETA from Z and SE Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 13 SNPs (52%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887e7c627d.tsv.gz Summary statistics report: - 25 rows (100% of original 25 rows) - 25 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ Z SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs12184267 1 715265 C T 0.9591931 -0.916 0.007518884 0.3598 2: rs12184277 1 715367 A G 0.9589313 -0.656 0.007491601 0.5116 3: rs12184279 1 717485 C A 0.9594241 -1.050 0.007534860 0.2938 4: rs116801199 1 720381 G T 0.9578380 -0.300 0.007391344 0.7644 N BETA IMPUTATION_BETA <int> <num> <lgcl> 1: 225955 -0.006887298 TRUE 2: 226215 -0.004914490 TRUE 3: 226224 -0.007911603 TRUE 4: 226626 -0.002217403 TRUE Returning path to saved data. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Sorting coordinates with 'data.table'. Filtering SNPs based on INFO score. 46 SNPs are below the INFO threshold of 0.9 and will be removed. Writing in tabular format ==> /tmp/RtmpfQlZhL/info_filter.tsv.gz INFO_filter==0. Skipping INFO score filtering step. Filtering SNPs based on INFO score. All rows have INFO>=0.9 Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Sorting coordinates with 'data.table'. 3 p-values are >1 which LDSC/MAGMA may not be able to handle. These will be converted to 1. 5 p-values are <0 which LDSC/MAGMA may not be able to handle. These will be converted to 0. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Sorting coordinates with 'data.table'. 8 p-values are <=5e-324 which LDSC/MAGMA may not be able to handle. These will be converted to 0. Reading header. Tabular format detected. Reading header. Tabular format detected. Reading header. Tabular format detected. Reading header. VCF format detected.This will be converted to a standardised table format. Importing tabular file: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/library/MungeSumstats/extdata/eduAttainOkbay.txt Checking for empty columns. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Computing Z-score from P using formula: `sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE)` Standardising column headers. First line of summary statistics file: SNP CHR BP A1 A2 FRQ BETA SE P Z newZ Computing Z-score from BETA ans SE using formula: `BETA/SE` ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39883623b851.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398859b3f719 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName EAF Beta SE Pval CHR_BP_A2_A1 Standardising column headers. First line of summary statistics file: MarkerName EAF Beta SE Pval CHR_BP_A2_A1 Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Column CHR_BP_A2_A1 has been separated into the columns CHR, BP, A2, A1 If this is the incorrect format for the column, update the column name to the correct format e.g.`CHR:BP:A2:A1` and format_sumstats(). Standardising column headers. First line of summary statistics file: SNP FRQ BETA SE P CHR BP A2 A1 Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39883623b851.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.105 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39888178cc.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398859b3f719 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39888178cc.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39885ab7a1fa.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39883bd3fdbd Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName EAF Beta SE Pval CHR_BP_A2_A1 Standardising column headers. First line of summary statistics file: MarkerName EAF Beta SE Pval CHR_BP_A2_A1 Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Column CHR_BP_A2_A1 has been separated into the columns CHR, BP, A2, A1 If this is the incorrect format for the column, update the column name to the correct format e.g.`CHR:BP:A2:A1` and format_sumstats(). Standardising column headers. First line of summary statistics file: SNP FRQ BETA SE P CHR BP A2 A1 Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39885ab7a1fa.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.104 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398870efe2f0.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39883bd3fdbd Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398870efe2f0.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39886c113360.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988502dc1d7 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS EAF Beta SE Pval alleles allele Standardising column headers. First line of summary statistics file: MarkerName CHR POS EAF Beta SE Pval alleles allele Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Warning: Multiple columns in the sumstats file seem to relate to alleles A1>A2. The column ALLELES will be kept whereas the column(s) ALLELE will be removed. If this is not the correct column to keep, please remove all incorrect columns from those listed here before running `format_sumstats()`. Column ALLELES has been separated into the columns A1, A2 Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39886c113360.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.052 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887ef818ad.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988502dc1d7 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887ef818ad.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988758183f0.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398863c46fb3 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval CHR_BP Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval CHR_BP Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Column CHR_BP has been separated into the columns CHR, BP Standardising column headers. First line of summary statistics file: SNP A1 A2 FRQ BETA SE P CHR BP Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988758183f0.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.08 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398835ad9ee0.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398863c46fb3 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398835ad9ee0.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988728af56a.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988341971fe Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval CHR_BP CHR_BP_2 Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval CHR_BP CHR_BP_2 Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Warning: Multiple columns in the sumstats file seem to relate to Chromosome:Base Pair position. The column CHR_BP_2 will be kept whereas the column(s) CHR_BP will be removed. If this is not the correct column to keep, please remove all incorrect columns from those listed here before running `format_sumstats()`. Column CHR_BP_2 has been separated into the columns CHR, BP Standardising column headers. First line of summary statistics file: SNP A1 A2 FRQ BETA SE P CHR BP Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988728af56a.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.106 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39885d55a32.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988341971fe Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39885d55a32.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.055 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887fce06fe.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39882e07c3e5 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887fce06fe.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398878a2fb49.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39883aafff50 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398878a2fb49.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. Setting sorted=FALSE (required when formatted=FALSE). ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398817d0fa0c.tsv.gz Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Assigning N=1000 for all SNPs. N already exists within sumstats_dt. [1] "Testing: compute_n='ldsc'" Computing effective sample size using the LDSC method: Neff = (N_CAS+N_CON) * (N_CAS/(N_CAS+N_CON)) / mean((N_CAS/(N_CAS+N_CON))[(N_CAS+N_CON)==max(N_CAS+N_CON)])) [1] "Testing: compute_n='giant'" Computing effective sample size using the GIANT method: Neff = 2 / (1/N_CAS + 1/N_CON) [1] "Testing: compute_n='metal'" Computing effective sample size using the METAL method: Neff = 4 / (1/N_CAS + 1/N_CON) [1] "Testing: compute_n='sum'" Computing sample size using the sum method: N = N_CAS + N_CON ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39886e1bdb88.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988577d772f Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39886e1bdb88.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398835c5003d.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Saving output messages to: /tmp/RtmpfQlZhL/file398835c5003d_log_msg.txt Any runtime errors will be saved to: /tmp/RtmpfQlZhL/file398835c5003d_log_output.txt Messages will not be printed to terminal. Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39882bf94445.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39887acd32d7 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39882bf94445.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398872167be7.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398816b995c0 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 186 rows - 93 unique variants - 140 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. 93 sumstat rows are duplicated. These duplicates will be removed. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398872167be7.tsv.gz Summary statistics report: - 93 rows (50% of original 186 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398858a3cdf1.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398816b995c0 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398858a3cdf1.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398839c04e93.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398816b995c0 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 94 rows - 94 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicate SNPs from SNP ID. Checking for SNPs with duplicated base-pair positions. 1 base-pair positions are duplicated in the sumstats file. These duplicates will be removed. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Checking for bi-allelic SNPs. Loading SNPlocs data. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 93 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 21 seconds. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398839c04e93.tsv.gz Summary statistics report: - 93 rows (98.9% of original 94 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.417 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988729dbf42.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39884138b799 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Filtering effect columns, ensuring none equal 0. 5 SNPs have effect values = 0 and will be removed Ensuring all SNPs have N<5 std dev above mean. 44 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988729dbf42.tsv.gz Summary statistics report: - 88 rows (94.6% of original 93 rows) - 88 unique variants - 65 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.057 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39885daeb63b.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398873ef35b3 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval FRQ Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval FRQ Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs based on FRQ. 38 SNPs are below the FRQ threshold of 0.9 and will be removed. Writing in tabular format ==> /tmp/RtmpfQlZhL/frq_filter.tsv.gz Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 55 SNPs (100%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39885daeb63b.tsv.gz Summary statistics report: - 55 rows (59.1% of original 93 rows) - 55 unique variants - 41 genome-wide significant variants (P<5e-8) - 16 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 EAF BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 2: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3: rs1008078 1 91189731 T C 0.37310 -0.016 0.003 6.005e-10 4: rs61787263 1 98618714 T C 0.76120 0.016 0.003 5.391e-08 FRQ <num> 1: 1.863269 2: 1.169733 3: 1.401423 4: 1.873332 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398823d2e526.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398873ef35b3 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval FRQ Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval FRQ Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs based on FRQ. 38 SNPs are below the FRQ threshold of 0.9 and will be removed. Writing in tabular format ==> /tmp/RtmpfQlZhL/frq_filter.tsv.gz Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 55 SNPs (100%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=FALSE, the FRQ column will be renamed MAJOR_ALLELE_FRQ to differentiate the values from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398823d2e526.tsv.gz Summary statistics report: - 55 rows (59.1% of original 93 rows) - 55 unique variants - 41 genome-wide significant variants (P<5e-8) - 16 chromosomes Done munging in 0.058 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 EAF BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 2: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3: rs1008078 1 91189731 T C 0.37310 -0.016 0.003 6.005e-10 4: rs61787263 1 98618714 T C 0.76120 0.016 0.003 5.391e-08 MAJOR_ALLELE_FRQ <num> 1: 1.863269 2: 1.169733 3: 1.401423 4: 1.873332 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884f7adc30.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988404aef7 Checking for empty columns. Infer Effect Column First line of summary statistics file: SNP CHR BP A1 A2 FRQ BETA SE P Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: SNP CHR BP A1 A2 FRQ BETA SE P Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39884f7adc30.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.044 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988114d942a.tsv Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. Removing temporary .tsv file. Reading header. Reading entire file. Sorting coordinates with 'GenomicRanges'. Converting summary statistics to GenomicRanges. Sorting coordinates with 'data.table'. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398819354c23.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988700023e7 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval INFO Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval INFO Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. Filtering SNPs based on INFO score. 38 SNPs are below the INFO threshold of 0.9 and will be removed. Writing in tabular format ==> /tmp/RtmpfQlZhL/info_filter.tsv.gz Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 28 SNPs (50.9%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398819354c23.tsv.gz Summary statistics report: - 55 rows (59.1% of original 93 rows) - 55 unique variants - 41 genome-wide significant variants (P<5e-8) - 16 chromosomes Done munging in 0.039 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 2: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3: rs1008078 1 91189731 T C 0.37310 -0.016 0.003 6.005e-10 4: rs61787263 1 98618714 T C 0.76120 0.016 0.003 5.391e-08 INFO <num> 1: 1.863269 2: 1.169733 3: 1.401423 4: 1.873332 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884d2428d.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398844299091 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39884d2428d.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.04 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39885160c28c.tsv.gz Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39885160c28c.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. [1] "/tmp/RtmpfQlZhL/data/file1/file398874d926c5.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file2/file39885c808b71.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file3/file39887b42d728.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file4/file3988613bc250.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file5/file39881a52440f.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file6/file3988ef24249.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file7/file398842ddce49.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file8/file398870123cea.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file9/file39883d5d6021.tsv.gz" [1] "/tmp/RtmpfQlZhL/data/file10/file39883d523600.tsv.gz" 10 file(s) found. Parsing info from 10 log file(s). ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39881015deff.tsv.gz sumstats has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval_org LP P Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval_org LP P Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39881015deff.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE PVAL_ORG <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 LP P <num> <num> 1: 7.746178 1.794e-08 2: 9.627272 2.359e-10 3: 13.424581 3.762e-14 4: 7.745452 1.797e-08 Returning data directly. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398821b63356.tsv.gz sumstats has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval_org LP P Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval_org LP P Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398821b63356.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.043 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE PVAL_ORG <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 LP P <num> <num> 1: -7.746178 1.794e-08 2: -9.627272 2.359e-10 3: -13.424581 3.762e-14 4: -7.745452 1.797e-08 Returning data directly. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887ba4b057.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39884165b26b Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. WARNING: 1 rows in sumstats file are missing data and will be removed. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887ba4b057.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.037 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs10061788 5 87934707 A G 0.2164 0.021 0.004 2.464e-09 2: rs1007883 16 51163406 T C 0.3713 -0.015 0.003 5.326e-08 3: rs1008078 1 91189731 T C 0.3731 -0.016 0.003 6.005e-10 4: rs1043209 14 23373986 A G 0.6026 0.018 0.003 1.816e-11 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988b1de6c.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39884165b26b Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988b1de6c.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.052 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs10061788 5 87934707 A G 0.2164 0.021 0.004 2.464e-09 2: rs1007883 16 51163406 T C 0.3713 -0.015 0.003 5.326e-08 3: rs1008078 1 91189731 T C 0.3731 -0.016 0.003 6.005e-10 4: rs1043209 14 23373986 A G 0.6026 0.018 0.003 1.816e-11 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988435cea17.tsv.gz Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 21 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Loading SNPlocs data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 1 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 2 seconds. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988435cea17.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.1 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs10061788 5 87934707 A G 0.2164 0.021 0.004 2.464e-09 2: rs1007883 16 51163406 T C 0.3713 -0.015 0.003 5.326e-08 3: rs1008078 1 91189731 T C 0.3731 -0.016 0.003 6.005e-10 4: rs1043209 14 23373986 A G 0.6026 0.018 0.003 1.816e-11 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39882ecfd72f.tsv.gz Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval extra Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval extra Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 21 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Loading SNPlocs data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 1 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 2 seconds. Checking for missing data. WARNING: 93 rows in sumstats file are missing data and will be removed. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887fdc8d2e.tsv.gz Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval extra Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval extra Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 21 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Loading SNPlocs data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 1 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 3 seconds. Checking for missing data. WARNING: None of the inputted columns: CHRA APOS To be checked for missing data were found in the sumstats. Sumstats columns: SNP CHR BP A1 A2 FRQ BETA SE P EXTRA This check will not be run. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887fdc8d2e.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.124 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P EXTRA <char> <int> <int> <char> <char> <num> <num> <num> <num> <lgcl> 1: rs10061788 5 87934707 A G 0.2164 0.021 0.004 2.464e-09 NA 2: rs1007883 16 51163406 T C 0.3713 -0.015 0.003 5.326e-08 NA 3: rs1008078 1 91189731 T C 0.3731 -0.016 0.003 6.005e-10 NA 4: rs1043209 14 23373986 A G 0.6026 0.018 0.003 1.816e-11 NA Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398820b05bd7.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398863ee097a Checking for empty columns. Infer Effect Column First line of summary statistics file: chromosome rs_id markername position_hg18 Effect_allele Other_allele EAF_HapMapCEU N_SMK Effect_SMK StdErr_SMK P_value_SMK N_NONSMK Effect_NonSMK StdErr_NonSMK P_value_NonSMK Standardising column headers. First line of summary statistics file: chromosome rs_id markername position_hg18 Effect_allele Other_allele EAF_HapMapCEU N_SMK Effect_SMK StdErr_SMK P_value_SMK N_NONSMK Effect_NonSMK StdErr_NonSMK P_value_NonSMK Summary statistics report: - 5 rows - 5 unique variants - 1 chromosomes Checking for multi-GWAS. WARNING: Multiple traits found in sumstats file only one of which can be analysed: SMK, NONSMK Standardising column headers. First line of summary statistics file: CHR SNP MARKERNAME POSITION_HG18 A2 A1 EAF_HAPMAPCEU N EFFECT STDERR P_VALUE N_NONSMK EFFECT_NONSMK STDERR_NONSMK P_VALUE_NONSMK Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs are not correctly formatted and will be removed. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Column MARKERNAME has been separated into the columns CHR, BP Standardising column headers. First line of summary statistics file: CHR SNP POSITION_HG18 A2 A1 EAF_HAPMAPCEU N BETA SE P N_NONSMK EFFECT_NONSMK STDERR_NONSMK P_VALUE_NONSMK BP Checking for incorrect base-pair positions Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Ensuring that the N column is all integers. The sumstats N column is not all integers, this could effect downstream analysis. These will be converted to integers. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398820b05bd7.tsv.gz Summary statistics report: - 4 rows (80% of original 5 rows) - 4 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Done munging in 0.156 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 POSITION_HG18 EAF_HAPMAPCEU N <char> <char> <int> <char> <char> <int> <num> <int> 1: rs1000050 chr1 161003087 C T 161003087 0.9000 36257 2: rs1000073 chr1 155522020 G A 155522020 0.3136 36335 3: rs1000075 chr1 94939420 C T 94939420 0.3583 38959 4: rs1000085 chr1 66630503 G C 66630503 0.1667 38761 BETA SE P N_NONSMK EFFECT_NONSMK STDERR_NONSMK P_VALUE_NONSMK <num> <num> <num> <int> <num> <num> <num> 1: 0.0001 0.0109 0.9931 127514 0.0058 0.0059 0.3307 2: 0.0046 0.0083 0.5812 126780 0.0038 0.0045 0.3979 3: -0.0013 0.0082 0.8687 147567 -0.0043 0.0044 0.3259 4: 0.0053 0.0095 0.5746 147259 -0.0034 0.0052 0.5157 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887bc4d41b.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39886c4e1ad9 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N N_fixed Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N N_fixed Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Ensuring that the N column is all integers. The sumstats N column is not all integers, this could effect downstream analysis. These will be converted to integers. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887bc4d41b.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N <char> <int> <int> <char> <char> <num> <num> <num> <num> <int> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 5 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 1 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 1 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 7 N_FIXED <int> 1: 5 2: 1 3: 1 4: 7 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398810e1c227.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39882935e35c Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 1 SNPs have N values 5 standard deviations above the mean and will be removed Writing in tabular format ==> /tmp/RtmpfQlZhL/n_large.tsv.gz 47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398810e1c227.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N <char> <int> <int> <char> <char> <num> <num> <num> <num> <int> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 3 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 5 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 3 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884e37ba79.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39882935e35c Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 1 SNPs have N values 5 standard deviations above the mean and will be removed Writing in tabular format ==> /tmp/RtmpfQlZhL/n_large.tsv.gz 47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39884e37ba79.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N <char> <int> <int> <char> <char> <num> <num> <num> <num> <int> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 3 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 5 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 3 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988667f764c.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39882935e35c Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval N Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 1 SNPs have N values 5 standard deviations above the mean and will be removed Writing in tabular format ==> /tmp/RtmpfQlZhL/n_large.tsv.gz Removing rows where is.na(N) 0 SNPs have N values that are NA and will be removed. Writing in tabular format ==> /tmp/RtmpfQlZhL/n_null.tsv.gz 47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988667f764c.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.057 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P N <char> <int> <int> <char> <char> <num> <num> <num> <num> <int> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 3 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 5 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 3 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 3 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398824eb2f67.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39886065751a Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Standardising column headers. First line of summary statistics file: SNP BP A1 A2 FRQ BETA SE P Loading SNPlocs data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 93 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 21 seconds. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398824eb2f67.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.481 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884f2db7a0.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398865e7b544 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Standardising column headers. First line of summary statistics file: SNP A1 A2 FRQ BETA SE P Loading SNPlocs data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 93 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 20 seconds. Writing in tabular format ==> /tmp/RtmpfQlZhL/chr_bp_not_found_from_snp.tsv.gz Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39884f2db7a0.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.472 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988922217e.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39885d322ce7 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs are not correctly formatted. These will be corrected from the reference genome. Loading SNPlocs data. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Coercing BP column to numeric. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988922217e.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.063 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39886467c00d.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39885d322ce7 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39886467c00d.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39883be8c32d.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398841f51d79 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs appear to be made up of chr:bp, these will be replaced by their SNP ID from the reference genome Loading SNPlocs data. 1 SNP IDs are not correctly formatted and will be removed. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column. Standardising column headers. First line of summary statistics file: SNP A1 A2 FRQ BETA SE P Loading SNPlocs data. There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information. Loading reference genome data. Preprocessing RSIDs. Validating RSIDs of 92 SNPs using BSgenome::snpsById... BSgenome::snpsById done in 20 seconds. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39883be8c32d.tsv.gz Summary statistics report: - 92 rows (98.9% of original 93 rows) - 92 unique variants - 69 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.457 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887dbad1e2.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988436214c3 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 1 SNP IDs are not correctly formatted. These will be corrected from the reference genome. Loading SNPlocs data. 1 SNP IDs appear to be made up of chr:bp, these will be replaced by their SNP ID from the reference genome Loading SNPlocs data. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Coercing BP column to numeric. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887dbad1e2.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.061 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39882160aa22.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39885c4130c4 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39882f5bd041.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398841f51d79 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39882f5bd041.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887552aa25.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988224f12ab Checking for empty columns. Infer Effect Column First line of summary statistics file: CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Loading SNPlocs data. There is no SNP column found within the data. It must be inferred from other column information. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887552aa25.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.116 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39882a323845.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39887c1a6a32 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 23 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions 1 SNPs have been removed as their BP column is not in the range of 1 to the length of the chromosome Writing in tabular format ==> /tmp/RtmpfQlZhL/bad_bp.tsv.gz Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 2 SNPs are on chromosomes X, Y, MT and will be removed. Writing in tabular format ==> /tmp/RtmpfQlZhL/chr_excl.tsv.gz 45 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39882a323845.tsv.gz Summary statistics report: - 90 rows (96.8% of original 93 rows) - 90 unique variants - 67 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.055 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39883b954578.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39887c1a6a32 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39883b954578.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. Reading header. Reading entire file. Reading header. Reading header. Reading header. Reading header. Reading header. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39886554216d Checking for empty columns. Standardising column headers. First line of summary statistics file: SNP CHR BP A1 A2 FRQ BETA SE P Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39884238451b Checking for empty columns. Standardising column headers. First line of summary statistics file: SNP CHR BP A1 A2 FRQ BETA SE P ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398813e909a0.vcf.bgz Sorting coordinates with 'data.table'. Converting summary statistics to GenomicRanges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpfQlZhL/file398813e909a0.vcf.bgz Using local VCF. Finding empty VCF columns based on first 10,000 rows. 1 sample detected: GWAS Constructing ScanVcfParam object. Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Checking for empty columns. Time difference of 0.1 secs VCF data.table contains: 93 rows x 11 columns. Time difference of 0.4 secs No INFO (SI) column detected. Standardising column headers. First line of summary statistics file: ID chr BP end REF ALT SNP FRQ BETA SE P Using local VCF. bgzip-compressing VCF file. Finding empty VCF columns based on first 10,000 rows. Dropping 1 duplicate column(s). 1 sample detected: EBI-a-GCST005647 Constructing ScanVcfParam object. VCF contains: 39,630,630 variant(s) x 1 sample(s) Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Dropping 1 duplicate column(s). Checking for empty columns. Unlisting 3 columns. Dropped 314 duplicate rows. Time difference of 0.1 secs VCF data.table contains: 101 rows x 11 columns. Time difference of 0.5 secs Renaming ID as SNP. sumstats has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. No INFO (SI) column detected. Standardising column headers. First line of summary statistics file: SNP chr BP end REF ALT FILTER AF ES LP SE P ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988106a8c6.vcf.bgz Sorting coordinates with 'data.table'. Converting summary statistics to GenomicRanges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpfQlZhL/file3988106a8c6.vcf.bgz Using local VCF. Finding empty VCF columns based on first 10,000 rows. 1 sample detected: GWAS Constructing ScanVcfParam object. Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Checking for empty columns. Time difference of 0.1 secs VCF data.table contains: 101 rows x 13 columns. Time difference of 0.4 secs sumstats has -log10 P-values; these will be converted to unadjusted p-values in the 'P' column. No INFO (SI) column detected. Standardising column headers. First line of summary statistics file: ID chr BP end REF SNP END FILTER FRQ BETA LP SE P ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39883e5ab9d7.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Infer Effect Column First line of summary statistics file: SNP P FRQ BETA CHR BP Standardising column headers. First line of summary statistics file: SNP P FRQ BETA CHR BP Summary statistics report: - 5 rows - 5 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. 5 SNP IDs contain other information in the same column. These will be separated. Checking for merged allele column. Column SNP_INFO has been separated into the columns A1, A2 Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Coercing BP column to numeric. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. SE is not present but can be imputed with BETA & P. Set impute_se=TRUE and rerun to do this. Ensuring all SNPs have N<5 std dev above mean. 3 SNPs (60%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39883e5ab9d7.tsv.gz Summary statistics report: - 5 rows (100% of original 5 rows) - 5 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Done munging in 0.051 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 P FRQ BETA <char> <int> <int> <char> <char> <num> <num> <num> 1: rs140052487 1 54353 C A 0.037219838 0.3000548 0.8797957 2: rs558796213 1 54564 G T 0.004382482 0.5848666 0.7068747 3: rs561234294 1 54591 A G 0.070968402 0.3334671 0.7319726 4: rs2462492 1 54676 C T 0.065769040 0.6220120 0.9316344 Returning data directly. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** ******::NOTE::****** - Log results will be saved to `tempdir()` by default. - This means all log data from the run will be deleted upon ending the R session. - To keep it, change `log_folder` to an actual directory (e.g. log_folder='./'). ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398813715d07.tsv.gz Log data to be saved to ==> /tmp/RtmpfQlZhL Infer Effect Column First line of summary statistics file: SNP P FRQ BETA CHR BP A1 A2 Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: SNP P FRQ BETA CHR BP A1 A2 Summary statistics report: - 5 rows - 5 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Coercing BP column to numeric. Reordering so first three column headers are SNP, CHR and BP in this order. Reordering so the fourth and fifth columns are A1 and A2. Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. SE is not present but can be imputed with BETA & P. Set impute_se=TRUE and rerun to do this. Ensuring all SNPs have N<5 std dev above mean. 3 SNPs (60%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398813715d07.tsv.gz Summary statistics report: - 5 rows (100% of original 5 rows) - 5 unique variants - 0 genome-wide significant variants (P<5e-8) - 1 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 P FRQ BETA <char> <int> <int> <char> <char> <num> <num> <num> 1: rs140052487 1 54353 C A 0.037219838 0.3000548 0.8797957 2: rs558796213 1 54564 G T 0.004382482 0.5848666 0.7068747 3: rs561234294 1 54591 A G 0.070968402 0.3334671 0.7319726 4: rs2462492 1 54676 C T 0.065769040 0.6220120 0.9316344 Returning data directly. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39881b99bcba.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988653580c7 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398826304588.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39882b4a788c Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398826304588.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39881eb55103.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39882b4a788c Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39881eb55103.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988796d548f.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39885008eac5 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file3988796d548f.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398852cca8c6.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39881fa81066 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. 47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398852cca8c6.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39887b7330fc.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39883c85e8be Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. 5 SNPs have SE values <= 0 and will be removed Ensuring all SNPs have N<5 std dev above mean. 44 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887b7330fc.tsv.gz Summary statistics report: - 88 rows (94.6% of original 93 rows) - 88 unique variants - 65 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Support Returning unmapped column names without making them uppercase. Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Support Returning unmapped column names without making them uppercase. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39881b0285e9.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39882a4ae508 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 85 rows - 85 unique variants - 63 genome-wide significant variants (P<5e-8) - 19 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Checking for strand ambiguous SNPs. 43 SNPs (50.6%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39881b0285e9.tsv.gz Summary statistics report: - 85 rows (100% of original 85 rows) - 85 unique variants - 63 genome-wide significant variants (P<5e-8) - 19 chromosomes Done munging in 0.054 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884513b504.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file39882a4ae508 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Checking for strand ambiguous SNPs. 8 SNPs are strand-ambiguous alleles including 4 A/T and 4 C/G ambiguous SNPs. These will be removed 43 SNPs (50.6%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency. The FRQ column was mapped from one of the following from the inputted summary statistics file: FRQ, EAF, FREQUENCY, FRQ_U, F_U, MAF, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF, ALLELEFREQ, ALT_FREQ, EAF_HRC, EFFECTALLELEFREQ, FREQ.B, FREQ_EUROPEAN_1000GENOMES, FREQ_HAPMAP, FREQ_TESTED_ALLELE_IN_HRS, FRQ_U_113154, FRQ_U_31358, FRQ_U_344901, FRQ_U_43456, POOLED_ALT_AF, AF_ALT, AF.ALT, AF-ALT, ALT.AF, ALT-AF, A2.AF, A2-AF, AF.EFF, AF_EFF, ALL_AF As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency, set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39884513b504.tsv.gz Summary statistics report: - 85 rows (91.4% of original 93 rows) - 85 unique variants - 63 genome-wide significant variants (P<5e-8) - 19 chromosomes Done munging in 0.053 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 FRQ BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning path to saved data. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398828e25810.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884d5bd26b.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file3988c1c9696 Checking for empty columns. Non-standard mapping file detected.Making sure all entries in `Uncorrected` are in upper case. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Summary statistics report: - 93 rows - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Checking for missing data. Checking for duplicate columns. Checking for duplicated rows. INFO column not available. Skipping INFO score filtering step. Filtering SNPs, ensuring SE>0. Ensuring all SNPs have N<5 std dev above mean. Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39884d5bd26b.tsv.gz Summary statistics report: - 93 rows (100% of original 93 rows) - 93 unique variants - 70 genome-wide significant variants (P<5e-8) - 20 chromosomes Done munging in 0.043 minutes. Successfully finished preparing sumstats file, preview: Reading header. SNP CHR BP A1 A2 EAF BETA SE P <char> <int> <int> <char> <char> <num> <num> <num> <num> 1: rs301800 1 8490603 T C 0.17910 0.019 0.003 1.794e-08 2: rs11210860 1 43982527 A G 0.36940 0.017 0.003 2.359e-10 3: rs34305371 1 72733610 A G 0.08769 0.035 0.005 3.762e-14 4: rs2568955 1 72762169 T C 0.23690 -0.017 0.003 1.797e-08 Returning data directly. Converting summary statistics to GenomicRanges. ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398821514616.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39885ed05f70.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884229e2b1.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884be1f466.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39885f747b75.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398858556f48.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398850fd0d46.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398815729834.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file3988166688ec.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398825a74971.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39889c6ad07.tsv.gz ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39884b7b7af0.tsv.gz Reading header. Tabular format detected. Importing tabular file: /tmp/RtmpfQlZhL/file398827840174 Checking for empty columns. Infer Effect Column First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Allele columns are ambiguous, attempting to infer direction Can't infer allele columns from sumstats Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Summary statistics report: - 93 rows - 93 unique variants - 20 chromosomes Checking for multi-GWAS. Checking for multiple RSIDs on one row. Checking SNP RSIDs. Checking for merged allele column. Checking A1 is uppercase Checking A2 is uppercase Checking for incorrect base-pair positions Standardising column headers. First line of summary statistics file: MarkerName CHR POS A1 A2 EAF Beta SE Pval Sorting coordinates with 'data.table'. .tsv === write tests === Writing in tabular format ==> /tmp/RtmpfQlZhL/file39887c47188.tsv === read tests === Importing tabular file: /tmp/RtmpfQlZhL/file39887c47188.tsv Checking for empty columns. .tsv.gz === write tests === Writing in tabular format ==> /tmp/RtmpfQlZhL/file39883e153fb6.tsv.gz === read tests === Importing tabular file: /tmp/RtmpfQlZhL/file39883e153fb6.tsv.gz Checking for empty columns. .tsv.bgz === write tests === Writing in tabular format ==> /tmp/RtmpfQlZhL/file39886e3050b3.tsv.bgz === read tests === Importing tabular bgz file: /tmp/RtmpfQlZhL/file39886e3050b3.tsv.bgz Checking for empty columns. .tsv.gz === write tests === Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file39884ac9f219.tsv Writing uncompressed instead of gzipped to enable tabix indexing. Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. Removing temporary .tsv file. === read tests === Importing tabular bgz file: /tmp/RtmpfQlZhL/file39884ac9f219.tsv.bgz Checking for empty columns. .tsv.bgz === write tests === Sorting coordinates with 'data.table'. Writing in tabular format ==> /tmp/RtmpfQlZhL/file398872afd9ca.tsv Writing uncompressed instead of gzipped to enable tabix indexing. Converting full summary stats file to tabix format for fast querying... Reading header. Ensuring file is bgzipped. Tabix-indexing file. Removing temporary .tsv file. === read tests === Importing tabular bgz file: /tmp/RtmpfQlZhL/file398872afd9ca.tsv.bgz Checking for empty columns. .csv === write tests === Writing in tabular format ==> /tmp/RtmpfQlZhL/file398851850780.csv === read tests === Importing tabular file: /tmp/RtmpfQlZhL/file398851850780.csv Checking for empty columns. .csv.gz === write tests === Writing in tabular format ==> /tmp/RtmpfQlZhL/file398818d8a4c8.csv.gz === read tests === Importing tabular file: /tmp/RtmpfQlZhL/file398818d8a4c8.csv.gz Checking for empty columns. .vcf === write tests === ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** save_path suggests VCF output but write_vcf=FALSE. Switching output to tabular format (.tsv.gz). Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file398871ac9b83.tsv.gz Writing in tabular format ==> /tmp/RtmpfQlZhL/file398871ac9b83.tsv.gz === read tests === Importing tabular file: /tmp/RtmpfQlZhL/file398871ac9b83.tsv.gz Checking for empty columns. .vcf.gz === write tests === ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** save_path suggests VCF output but write_vcf=FALSE. Switching output to tabular format (.tsv.gz). Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39885d4ab06d.tsv.gz Writing in tabular format ==> /tmp/RtmpfQlZhL/file39885d4ab06d.tsv.gz === read tests === Importing tabular file: /tmp/RtmpfQlZhL/file39885d4ab06d.tsv.gz Checking for empty columns. .vcf === write tests === Sorting coordinates with 'data.table'. Converting summary statistics to GenomicRanges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpfQlZhL/file398875c69c4d.vcf === read tests === Using local VCF. bgzip-compressing VCF file. Finding empty VCF columns based on first 10,000 rows. 1 sample detected: GWAS Constructing ScanVcfParam object. Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Checking for empty columns. Time difference of 0.1 secs VCF data.table contains: 93 rows x 11 columns. Time difference of 0.4 secs No INFO (SI) column detected. .vcf.gz === write tests === Sorting coordinates with 'data.table'. Converting summary statistics to GenomicRanges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpfQlZhL/file39886612ac04.vcf.gz === read tests === Using local VCF. Finding empty VCF columns based on first 10,000 rows. 1 sample detected: GWAS Constructing ScanVcfParam object. Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Checking for empty columns. Time difference of 0.1 secs VCF data.table contains: 93 rows x 11 columns. Time difference of 0.4 secs No INFO (SI) column detected. .vcf === write tests === Sorting coordinates with 'data.table'. Converting summary statistics to GenomicRanges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpfQlZhL/file398864b5ad1e.vcf .vcf === write tests === ******::NOTE::****** - Formatted results will be saved to `tempdir()` by default. - This means all formatted summary stats will be deleted upon ending the R session. - To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ), or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`. ******************** Formatted summary statistics will be saved to ==> /tmp/RtmpfQlZhL/file39883adaac01.vcf.bgz Sorting coordinates with 'data.table'. Converting summary statistics to GenomicRanges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpfQlZhL/file39883adaac01.vcf.bgz === read tests === Using local VCF. File already tabix-indexed. Finding empty VCF columns based on first 10,000 rows. 1 sample detected: GWAS Constructing ScanVcfParam object. Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Checking for empty columns. Time difference of 0.1 secs VCF data.table contains: 93 rows x 11 columns. Time difference of 0.4 secs No INFO (SI) column detected. .vcf.bgz === write tests === Sorting coordinates with 'data.table'. Converting summary statistics to GenomicRanges. Converting summary statistics to VRanges. Writing in VCF format ==> /tmp/RtmpfQlZhL/file398838c16f9.vcf.bgz === read tests === Using local VCF. File already tabix-indexed. Finding empty VCF columns based on first 10,000 rows. 1 sample detected: GWAS Constructing ScanVcfParam object. Reading VCF file: single-threaded Converting VCF to data.table. Expanding VCF first, so number of rows may increase. Checking for empty columns. Time difference of 0.1 secs VCF data.table contains: 93 rows x 11 columns. Time difference of 0.4 secs No INFO (SI) column detected. [ FAIL 0 | WARN 2 | SKIP 0 | PASS 161 ] [ FAIL 0 | WARN 2 | SKIP 0 | PASS 161 ] > > proc.time() user system elapsed 477.825 13.542 496.462
MungeSumstats.Rcheck/MungeSumstats-Ex.timings
name | user | system | elapsed | |
compute_nsize | 4.629 | 0.135 | 4.608 | |
download_vcf | 0.000 | 0.001 | 0.001 | |
find_sumstats | 0.001 | 0.001 | 0.002 | |
format_sumstats | 68.927 | 3.167 | 73.239 | |
formatted_example | 3.110 | 0.165 | 3.274 | |
get_genome_builds | 82.730 | 3.808 | 87.268 | |
import_sumstats | 0.001 | 0.000 | 0.002 | |
index_tabular | 3.130 | 0.207 | 3.338 | |
index_vcf | 3.041 | 0.020 | 3.061 | |
infer_effect_column | 4.393 | 0.135 | 4.558 | |
liftover | 3.913 | 0.042 | 4.226 | |
list_sumstats | 0.002 | 0.000 | 0.003 | |
load_snp_loc_data | 0.001 | 0.000 | 0.001 | |
parse_logs | 0.011 | 0.001 | 0.012 | |
read_header | 0.004 | 0.002 | 0.005 | |
read_sumstats | 0.006 | 0.001 | 0.006 | |
read_vcf | 1.658 | 0.018 | 1.677 | |
standardise_header | 3.060 | 0.012 | 3.073 | |
vcf2df | 0.487 | 0.012 | 0.499 | |
write_sumstats | 0.007 | 0.002 | 0.008 | |