Multiple platform build/check report for BioC 3.15 - CHECK results for SNPRelate on merida1

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo1	Linux (Ubuntu 20.04.5 LTS)	x86_64	4.2.1 (2022-06-23) -- "Funny-Looking Kid"	4386
palomino3	Windows Server 2022 Datacenter	x64	4.2.1 (2022-06-23 ucrt) -- "Funny-Looking Kid"	4138
merida1	macOS 10.14.6 Mojave	x86_64	4.2.1 (2022-06-23) -- "Funny-Looking Kid"	4205
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: SNPRelate

Version: 1.30.1

Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:SNPRelate.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings SNPRelate_1.30.1.tar.gz

StartedAt: 2022-10-19 08:15:37 -0400 (Wed, 19 Oct 2022)

EndedAt: 2022-10-19 08:18:27 -0400 (Wed, 19 Oct 2022)

EllapsedTime: 170.8 seconds

RetCode: 0

Status: OK

CheckDir: SNPRelate.Rcheck

Warnings: 0

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###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:SNPRelate.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings SNPRelate_1.30.1.tar.gz
###
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* using log directory ‘/Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck’
* using R version 4.2.1 (2022-06-23)
* using platform: x86_64-apple-darwin17.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘SNPRelate/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘SNPRelate’ version ‘1.30.1’
* 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 ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘SNPRelate’ 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 R 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 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 ... OK
* 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 line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking use of PKG_*FLAGS in Makefiles ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/00check.log’
for details.

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###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL SNPRelate
###
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* installing to library ‘/Library/Frameworks/R.framework/Versions/4.2/Resources/library’
* installing *source* package ‘SNPRelate’ ...
** using staged installation
** libs
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c ConvToGDS.cpp -o ConvToGDS.o
clang -mmacosx-version-min=10.13 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c R_SNPRelate.c -o R_SNPRelate.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c SNPRelate.cpp -o SNPRelate.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c ThreadPool.cpp -o ThreadPool.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c dGenGWAS.cpp -o dGenGWAS.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c dVect.cpp -o dVect.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genBeta.cpp -o genBeta.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genEIGMIX.cpp -o genEIGMIX.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genFst.cpp -o genFst.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genHWE.cpp -o genHWE.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genIBD.cpp -o genIBD.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genIBS.cpp -o genIBS.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genKING.cpp -o genKING.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genLD.cpp -o genLD.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genPCA.cpp -o genPCA.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -DUSING_R -DUSE_FC_LEN_T -I. -I'/Library/Frameworks/R.framework/Versions/4.2/Resources/library/gdsfmt/include' -I/usr/local/include   -fPIC  -Wall -g -O2  -c genSlideWin.cpp -o genSlideWin.o
clang++ -mmacosx-version-min=10.13 -std=gnu++14 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o SNPRelate.so ConvToGDS.o R_SNPRelate.o SNPRelate.o ThreadPool.o dGenGWAS.o dVect.o genBeta.o genEIGMIX.o genFst.o genHWE.o genIBD.o genIBS.o genKING.o genLD.o genPCA.o genSlideWin.o -lpthread -L/Library/Frameworks/R.framework/Resources/lib -lRlapack -L/Library/Frameworks/R.framework/Resources/lib -lRblas -L/usr/local/gfortran/lib/gcc/x86_64-apple-darwin18/8.2.0 -L/usr/local/gfortran/lib -lgfortran -lquadmath -lm -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.2/Resources/library/00LOCK-SNPRelate/00new/SNPRelate/libs
** 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
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (SNPRelate)


R version 4.2.1 (2022-06-23) -- "Funny-Looking Kid"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (64-bit)

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.

> BiocGenerics:::testPackage("SNPRelate")
SNPRelate -- supported by Streaming SIMD Extensions 2 (SSE2)
Genetic Relationship Matrix (GRM, GCTA):
Excluding 8,088 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 1,000
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 282597
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:16 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:17 2022    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 7,088 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 2,000
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 559412
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:17 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:18 2022    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 5,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 3,800
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1066957
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:18 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:19 2022    Done.
GRM merging:
    open 'tmp1.gds' (1,000 variants)
    open 'tmp2.gds' (2,000 variants)
    open 'tmp3.gds' (3,800 variants)
Weight: 0.147059, 0.294118, 0.558824
Output: tmp.gds

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Genetic Relationship Matrix (GRM, GCTA):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 6,800
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:20 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:20 2022    Done.
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 8,088 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 1,000
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 282597
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:20 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:21 2022    Done.
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 7,088 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 2,000
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 559412
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:21 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:17:22 2022    Done.
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 5,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 3,800
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1066957
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:22 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:22 2022    Done.
GRM merging:
    open 'tmp1.gds' (1,000 variants)
    open 'tmp2.gds' (2,000 variants)
    open 'tmp3.gds' (3,800 variants)
Weight: 0.147059, 0.294118, 0.558824
Output: tmp.gds

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Writing ...

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Genetic Relationship Matrix (GRM, IndivBeta):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 6,800
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:23 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:23 2022    Done.
Linkage Disequilibrium (LD) estimation on genotypes:
    # of samples: 279
    # of SNPs: 1,000
    using 1 thread
    method: covariance
LD matrix:    the sum of all selected genotypes (0,1,2) = 283058
Linkage Disequilibrium (LD) estimation on genotypes:
    # of samples: 279
    # of SNPs: 1,000
    using 1 thread
    method: correlation
LD matrix:    the sum of all selected genotypes (0,1,2) = 283058
FUNCTION: SNPGDSFileClass
FUNCTION: SNPRelate-package
Start file conversion from PLINK BED to SNP GDS ...
    BED file: '/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz'
        SNP-major mode (Sample X SNP), 45.7K
    FAM file: '/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz'
    BIM file: '/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz'
Wed Oct 19 08:17:29 2022     (store sample id, snp id, position, and chromosome)
    start writing: 60 samples, 5000 SNPs ...

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:29 2022 	Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'HapMap.gds' (98.1K)
    # of fragments: 38
    save to 'HapMap.gds.tmp'
    rename 'HapMap.gds.tmp' (97.8K, reduced: 240B)
    # of fragments: 18
Principal Component Analysis (PCA) on genotypes:
Excluding 203 SNPs on non-autosomes
Excluding 28 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 60
    # of SNPs: 4,769
    using 1 thread
    # of principal components: 32
PCA:    the sum of all selected genotypes (0,1,2) = 124273
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:29 2022    (internal increment: 64920)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:29 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:17:29 2022    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 19 08:17:29 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:29 2022    Done.
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 19 08:17:30 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:30 2022    Done.
Linkage Disequilibrium (LD) estimation on genotypes:
    # of samples: 279
    # of SNPs: 200
    using 1 thread
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 55417
FUNCTION: hapmap_geno
FUNCTION: snpgdsAdmixPlot
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:31 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:31 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:17:31 2022    Done.
FUNCTION: snpgdsAdmixProp
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:31 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:17:32 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:17:32 2022    Done.
FUNCTION: snpgdsAlleleSwitch
Strand-switching at 50 SNP locus/loci.
Unable to determine switching at 10 SNP locus/loci.
FUNCTION: snpgdsApartSelection
Wed Oct 19 08:17:32 2022	Chromosome 1, # of SNPs: 367
Wed Oct 19 08:17:32 2022	Chromosome 2, # of SNPs: 367
Wed Oct 19 08:17:32 2022	Chromosome 3, # of SNPs: 317
Wed Oct 19 08:17:32 2022	Chromosome 4, # of SNPs: 295
Wed Oct 19 08:17:32 2022	Chromosome 5, # of SNPs: 295
Wed Oct 19 08:17:32 2022	Chromosome 6, # of SNPs: 283
Wed Oct 19 08:17:32 2022	Chromosome 7, # of SNPs: 245
Wed Oct 19 08:17:32 2022	Chromosome 8, # of SNPs: 234
Wed Oct 19 08:17:32 2022	Chromosome 9, # of SNPs: 202
Wed Oct 19 08:17:32 2022	Chromosome 10, # of SNPs: 224
Wed Oct 19 08:17:32 2022	Chromosome 11, # of SNPs: 223
Wed Oct 19 08:17:33 2022	Chromosome 12, # of SNPs: 208
Wed Oct 19 08:17:33 2022	Chromosome 13, # of SNPs: 172
Wed Oct 19 08:17:33 2022	Chromosome 14, # of SNPs: 147
Wed Oct 19 08:17:33 2022	Chromosome 15, # of SNPs: 121
Wed Oct 19 08:17:33 2022	Chromosome 16, # of SNPs: 129
Wed Oct 19 08:17:33 2022	Chromosome 17, # of SNPs: 116
Wed Oct 19 08:17:33 2022	Chromosome 18, # of SNPs: 129
Wed Oct 19 08:17:33 2022	Chromosome 19, # of SNPs: 73
Wed Oct 19 08:17:33 2022	Chromosome 20, # of SNPs: 106
Wed Oct 19 08:17:33 2022	Chromosome 21, # of SNPs: 62
Wed Oct 19 08:17:33 2022	Chromosome 22, # of SNPs: 51
Wed Oct 19 08:17:33 2022	Chromosome 23, # of SNPs: 204
Total # of SNPs selected:4570
FUNCTION: snpgdsBED2GDS
Start file conversion from PLINK BED to SNP GDS ...
    BED file: '/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/plinkhapmap.bed.gz'
        SNP-major mode (Sample X SNP), 45.7K
    FAM file: '/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/plinkhapmap.fam.gz'
    BIM file: '/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/plinkhapmap.bim.gz'
Wed Oct 19 08:17:33 2022     (store sample id, snp id, position, and chromosome)
    start writing: 60 samples, 5000 SNPs ...

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:33 2022 	Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'HapMap.gds' (98.1K)
    # of fragments: 38
    save to 'HapMap.gds.tmp'
    rename 'HapMap.gds.tmp' (97.8K, reduced: 240B)
    # of fragments: 18
FUNCTION: snpgdsClose
FUNCTION: snpgdsCombineGeno
Create a GDS genotype file:
The new dataset consists of 10 samples and 3000 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Create a GDS genotype file:
The new dataset consists of 20 samples and 3000 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Merge SNP GDS files:
    open 't1.gds' ...
        10 samples, 3000 SNPs
    open 't2.gds' ...
        20 samples, 3000 SNPs
Concatenating samples (mapping to the first GDS file) ...
    reference: 3000 SNPs (100.0%)
    file 2: 0 allele flips, 0 ambiguous locus/loci
        [no flip]: 3000
    create 'test.gds': 30 samples, 3000 SNPs
    FileFormat = SNP_ARRAY
    writing genotypes ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (46.2K)
    # of fragments: 32
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (46.0K, reduced: 204B)
    # of fragments: 15
Done.
Create a GDS genotype file:
The new dataset consists of 279 samples and 100 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Create a GDS genotype file:
The new dataset consists of 279 samples and 200 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Merge SNP GDS files:
    open 't1.gds' ...
        279 samples, 100 SNPs
    open 't2.gds' ...
        279 samples, 200 SNPs
Concatenating SNPs ...
    create 'test.gds': 279 samples, 300 SNPs
    FileFormat = SNP_ARRAY
    writing genotypes ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (19.1K)
    # of fragments: 32
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (18.9K, reduced: 204B)
    # of fragments: 15
Done.
FUNCTION: snpgdsCreateGeno
Principal Component Analysis (PCA) on genotypes:
Excluding 42 SNPs on non-autosomes
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 958
    using 1 thread
    # of principal components: 32
PCA:    the sum of all selected genotypes (0,1,2) = 264760
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:33 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:17:34 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:17:34 2022    Done.
FUNCTION: snpgdsCreateGenoSet
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 76.12%, 545/716
Chromosome 2: 72.78%, 540/742
Chromosome 3: 74.71%, 455/609
Chromosome 4: 73.49%, 413/562
Chromosome 5: 76.86%, 435/566
Chromosome 6: 75.75%, 428/565
Chromosome 7: 75.42%, 356/472
Chromosome 8: 71.11%, 347/488
Chromosome 9: 77.88%, 324/416
Chromosome 10: 74.12%, 358/483
Chromosome 11: 77.85%, 348/447
Chromosome 12: 76.81%, 328/427
Chromosome 13: 76.16%, 262/344
Chromosome 14: 76.60%, 216/282
Chromosome 15: 76.34%, 200/262
Chromosome 16: 72.66%, 202/278
Chromosome 17: 73.91%, 153/207
Chromosome 18: 73.68%, 196/266
Chromosome 19: 85.00%, 102/120
Chromosome 20: 71.62%, 164/229
Chromosome 21: 76.98%, 97/126
Chromosome 22: 75.86%, 88/116
6,557 markers are selected in total.
Create a GDS genotype file:
The new dataset consists of 279 samples and 6557 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
FUNCTION: snpgdsCutTree
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Wed Oct 19 08:17:34 2022	0%
Dissimilarity:	Wed Oct 19 08:17:35 2022	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
Create 4 groups.
FUNCTION: snpgdsDiss
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Wed Oct 19 08:17:37 2022	0%
Dissimilarity:	Wed Oct 19 08:17:38 2022	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsDrawTree
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Wed Oct 19 08:17:40 2022	0%
Dissimilarity:	Wed Oct 19 08:17:41 2022	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsEIGMIX
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:42 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:42 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:17:42 2022    Done.
FUNCTION: snpgdsErrMsg
FUNCTION: snpgdsExampleFileName
FUNCTION: snpgdsFst
Fst estimation on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
Method: Weir & Cockerham, 1984
# of Populations: 4
    CEU (92), HCB (47), JPT (47), YRI (93)
Fst estimation on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
Method: Weir & Hill, 2002
# of Populations: 4
    CEU (92), HCB (47), JPT (47), YRI (93)
FUNCTION: snpgdsGDS2BED
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: 0.95)
Converting from GDS to PLINK binary PED:
Working space: 279 samples, 8722 SNPs
Output a BIM file.
Output a BED file ...
		Wed Oct 19 08:17:43 2022	0%
		Wed Oct 19 08:17:43 2022	100%
Done.
FUNCTION: snpgdsGDS2Eigen
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: 0.95)
Converting from GDS to EIGENSOFT:
	save to *.snp: 8722 snps
	save to *.ind: 279 samples
	Output: 	Wed Oct 19 08:17:43 2022	0%
	Output: 	Wed Oct 19 08:17:44 2022	100%
Done.
FUNCTION: snpgdsGDS2PED
Converting from GDS to PLINK PED:
	Output a MAP file DONE.
	Output a PED file ...
		Output: 	Wed Oct 19 08:17:44 2022	0%
		Output: 	Wed Oct 19 08:17:44 2022	100%
FUNCTION: snpgdsGEN2GDS
running snpgdsGEN2GDS ...
FUNCTION: snpgdsGRM
Genetic Relationship Matrix (GRM, GCTA):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:44 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:17:45 2022    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:45 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:46 2022    Done.
FUNCTION: snpgdsGetGeno
Genotype matrix: 1000 SNPs X 279 samples
Genotype matrix: 279 samples X 1000 SNPs
FUNCTION: snpgdsHCluster
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Wed Oct 19 08:17:46 2022	0%
Dissimilarity:	Wed Oct 19 08:17:48 2022	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsHWE
Keeping 716 SNPs according to chromosome 1
Excluding 160 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
FUNCTION: snpgdsIBDKING
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 92
    # of SNPs: 7,506
    using 1 thread
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:49 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:49 2022    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 92
    # of SNPs: 7,506
    using 1 thread
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:49 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:49 2022    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 92
    # of SNPs: 7,506
    using 1 thread
# of families: 20, and within- and between-family relationship are estimated differently.
Relationship inference in the presence of population stratification.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:51 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:51 2022    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 92
    # of SNPs: 7,506
    using 1 thread
Relationship inference in a homogeneous population.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
Wed Oct 19 08:17:51 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:17:52 2022    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 92
    # of SNPs: 7,506
    using 1 thread
Relationship inference in a homogeneous population.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
Wed Oct 19 08:17:52 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:52 2022    Done.
FUNCTION: snpgdsIBDMLE
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,581 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
    # of samples: 30
    # of SNPs: 7,142
    using 1 thread
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 54.75%, 392/716
Chromosome 2: 54.31%, 403/742
Chromosome 3: 55.99%, 341/609
Chromosome 4: 56.58%, 318/562
Chromosome 5: 56.36%, 319/566
Chromosome 6: 52.74%, 298/565
Chromosome 7: 56.14%, 265/472
Chromosome 8: 51.84%, 253/488
Chromosome 9: 54.81%, 228/416
Chromosome 10: 49.90%, 241/483
Chromosome 11: 54.81%, 245/447
Chromosome 12: 54.57%, 233/427
Chromosome 13: 53.49%, 184/344
Chromosome 14: 56.03%, 158/282
Chromosome 15: 54.58%, 143/262
Chromosome 16: 54.68%, 152/278
Chromosome 17: 55.56%, 115/207
Chromosome 18: 55.64%, 148/266
Chromosome 19: 66.67%, 80/120
Chromosome 20: 53.28%, 122/229
Chromosome 21: 50.79%, 64/126
Chromosome 22: 51.72%, 60/116
4,762 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 30
    # of SNPs: 250
    using 1 thread
MLE IBD:    the sum of all selected genotypes (0,1,2) = 7859
MLE IBD:	Wed Oct 19 08:17:52 2022	0%
MLE IBD:	Wed Oct 19 08:17:53 2022	100%
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 25
    # of SNPs: 250
    using 1 thread
Specifying allele frequencies, mean: 0.525, sd: 0.288
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6545
MLE IBD:	Wed Oct 19 08:17:53 2022	0%
MLE IBD:	Wed Oct 19 08:17:53 2022	100%
FUNCTION: snpgdsIBDMLELogLik
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,581 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
    # of samples: 30
    # of SNPs: 7,142
    using 1 thread
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 54.75%, 392/716
Chromosome 2: 54.31%, 403/742
Chromosome 3: 55.99%, 341/609
Chromosome 4: 56.58%, 318/562
Chromosome 5: 56.36%, 319/566
Chromosome 6: 52.74%, 298/565
Chromosome 7: 56.14%, 265/472
Chromosome 8: 51.84%, 253/488
Chromosome 9: 54.81%, 228/416
Chromosome 10: 49.90%, 241/483
Chromosome 11: 54.81%, 245/447
Chromosome 12: 54.57%, 233/427
Chromosome 13: 53.49%, 184/344
Chromosome 14: 56.03%, 158/282
Chromosome 15: 54.58%, 143/262
Chromosome 16: 54.68%, 152/278
Chromosome 17: 55.56%, 115/207
Chromosome 18: 55.64%, 148/266
Chromosome 19: 66.67%, 80/120
Chromosome 20: 53.28%, 122/229
Chromosome 21: 50.79%, 64/126
Chromosome 22: 51.72%, 60/116
4,762 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 30
    # of SNPs: 250
    using 1 thread
MLE IBD:    the sum of all selected genotypes (0,1,2) = 7859
MLE IBD:	Wed Oct 19 08:17:53 2022	0%
MLE IBD:	Wed Oct 19 08:17:54 2022	100%
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 25
    # of SNPs: 250
    using 1 thread
Specifying allele frequencies, mean: 0.525, sd: 0.288
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6545
MLE IBD:	Wed Oct 19 08:17:54 2022	0%
MLE IBD:	Wed Oct 19 08:17:54 2022	100%
FUNCTION: snpgdsIBDMoM
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 92
    # of SNPs: 7,506
    using 1 thread
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 702139
Wed Oct 19 08:17:54 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:54 2022    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 93
    # of SNPs: 8,160
    using 1 thread
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Wed Oct 19 08:17:54 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:54 2022    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 93
    # of SNPs: 8,160
    using 1 thread
Specifying allele frequencies, mean: 0.500, sd: 0.315
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Wed Oct 19 08:17:55 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:55 2022    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 25
    # of SNPs: 8,160
    using 1 thread
Specifying allele frequencies, mean: 0.500, sd: 0.315
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 203285
Wed Oct 19 08:17:55 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:55 2022    Done.
FUNCTION: snpgdsIBDSelection
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 93
    # of SNPs: 8,160
    using 1 thread
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Wed Oct 19 08:17:55 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:55 2022    Done.
FUNCTION: snpgdsIBS
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 19 08:17:55 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:55 2022    Done.
FUNCTION: snpgdsIBSNum
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 19 08:17:55 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:17:56 2022    Done.
FUNCTION: snpgdsIndInb
Estimating individual inbreeding coefficients:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
FUNCTION: snpgdsIndInbCoef
FUNCTION: snpgdsIndivBeta
Individual Inbreeding and Relatedness (beta estimator):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
Individual Beta:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:56 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:56 2022    Done.
FUNCTION: snpgdsLDMat
Linkage Disequilibrium (LD) estimation on genotypes:
    # of samples: 279
    # of SNPs: 203
    using 1 thread
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 56582
Linkage Disequilibrium (LD) estimation on genotypes:
    # of samples: 279
    # of SNPs: 203
    using 1 thread
    sliding window size: 203
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 56582
FUNCTION: snpgdsLDpair
FUNCTION: snpgdsLDpruning
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 76.12%, 545/716
Chromosome 2: 72.78%, 540/742
Chromosome 3: 74.71%, 455/609
Chromosome 4: 73.49%, 413/562
Chromosome 5: 76.86%, 435/566
Chromosome 6: 75.75%, 428/565
Chromosome 7: 75.42%, 356/472
Chromosome 8: 71.11%, 347/488
Chromosome 9: 77.88%, 324/416
Chromosome 10: 74.12%, 358/483
Chromosome 11: 77.85%, 348/447
Chromosome 12: 76.81%, 328/427
Chromosome 13: 76.16%, 262/344
Chromosome 14: 76.60%, 216/282
Chromosome 15: 76.34%, 200/262
Chromosome 16: 72.66%, 202/278
Chromosome 17: 73.91%, 153/207
Chromosome 18: 73.68%, 196/266
Chromosome 19: 85.00%, 102/120
Chromosome 20: 71.62%, 164/229
Chromosome 21: 76.98%, 97/126
Chromosome 22: 75.86%, 88/116
6,557 markers are selected in total.
List of 22
 $ chr1 : int [1:545] 1 2 4 5 7 10 12 14 15 16 ...
 $ chr2 : int [1:540] 717 718 719 720 721 723 724 725 726 727 ...
 $ chr3 : int [1:455] 1459 1460 1461 1464 1466 1468 1469 1471 1472 1473 ...
 $ chr4 : int [1:413] 2068 2069 2070 2071 2072 2074 2075 2076 2077 2078 ...
 $ chr5 : int [1:435] 2630 2631 2633 2635 2636 2637 2638 2640 2642 2643 ...
 $ chr6 : int [1:428] 3196 3197 3198 3200 3201 3204 3205 3206 3207 3208 ...
 $ chr7 : int [1:356] 3761 3762 3763 3766 3767 3768 3770 3771 3772 3773 ...
 $ chr8 : int [1:347] 4233 4234 4235 4236 4237 4238 4239 4240 4241 4242 ...
 $ chr9 : int [1:324] 4721 4722 4724 4727 4728 4730 4731 4732 4733 4735 ...
 $ chr10: int [1:358] 5138 5139 5140 5143 5144 5145 5146 5147 5148 5149 ...
 $ chr11: int [1:348] 5620 5621 5623 5624 5625 5626 5628 5629 5630 5631 ...
 $ chr12: int [1:328] 6067 6068 6069 6070 6073 6074 6075 6077 6078 6079 ...
 $ chr13: int [1:262] 6494 6497 6498 6499 6500 6501 6503 6505 6507 6509 ...
 $ chr14: int [1:216] 6840 6841 6842 6843 6844 6845 6846 6847 6848 6850 ...
 $ chr15: int [1:200] 7120 7121 7122 7124 7125 7126 7127 7128 7129 7130 ...
 $ chr16: int [1:202] 7382 7383 7384 7385 7387 7388 7389 7391 7392 7394 ...
 $ chr17: int [1:153] 7660 7661 7662 7663 7664 7665 7666 7667 7668 7669 ...
 $ chr18: int [1:196] 7867 7868 7869 7870 7871 7872 7873 7874 7875 7877 ...
 $ chr19: int [1:102] 8133 8135 8136 8137 8138 8139 8140 8141 8142 8144 ...
 $ chr20: int [1:164] 8253 8254 8257 8258 8259 8260 8261 8262 8265 8266 ...
 $ chr21: int [1:97] 8482 8484 8485 8486 8487 8488 8489 8490 8491 8492 ...
 $ chr22: int [1:88] 8608 8609 8610 8612 8613 8614 8615 8617 8618 8619 ...
FUNCTION: snpgdsMergeGRM
Genetic Relationship Matrix (GRM, GCTA):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 6,800
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:57 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:17:58 2022    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 5,688 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 3,400
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 951558
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:58 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:58 2022    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 5,688 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 3,400
    using 1 thread
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 957408
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:17:59 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Saving to the GDS file:

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:17:59 2022    Done.
GRM merging:
    open 'tmp1.gds' (3,400 variants)
    open 'tmp2.gds' (3,400 variants)
Weight: 0.5, 0.5
Output: tmp.gds

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
GRM merging:
    open 'tmp1.gds' (3,400 variants)
    open 'tmp2.gds' (3,400 variants)
Weight: 0.5, 0.5

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
FUNCTION: snpgdsOpen
FUNCTION: snpgdsOption
FUNCTION: snpgdsPCA
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
    # of principal components: 32
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:18:00 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:18:01 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:18:01 2022    Done.
FUNCTION: snpgdsPCACorr
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
    # of principal components: 32
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:18:01 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:18:02 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:18:02 2022    Done.
SNP Correlation:
    # of samples: 279
    # of SNPs: 9,088
    using 1 thread
Correlation:    the sum of all selected genotypes (0,1,2) = 2553065
Wed Oct 19 08:18:02 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:02 2022    Done.
SNP Correlation:
    # of samples: 279
    # of SNPs: 9,088
    using 1 thread
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 2553065
Wed Oct 19 08:18:02 2022

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:02 2022    Done.
FUNCTION: snpgdsPCASNPLoading
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
    # of principal components: 8
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:18:02 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:18:03 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:18:03 2022    Done.
SNP Loading:
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 19 08:18:03 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:03 2022    Done.
FUNCTION: snpgdsPCASampLoading
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
    # of principal components: 8
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Wed Oct 19 08:18:03 2022    (internal increment: 13960)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 1s
Wed Oct 19 08:18:04 2022    Begin (eigenvalues and eigenvectors)
Wed Oct 19 08:18:04 2022    Done.
SNP Loading:
    # of samples: 279
    # of SNPs: 8,722
    using 1 thread
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 2446510
Wed Oct 19 08:18:04 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:04 2022    Done.
Sample Loading:
    # of samples: 100
    # of SNPs: 8,722
    using 1 thread
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 878146
Wed Oct 19 08:18:04 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:04 2022    Done.
FUNCTION: snpgdsPED2GDS
Converting from GDS to PLINK PED:
	Output a MAP file DONE.
	Output a PED file ...
		Output: 	Wed Oct 19 08:18:04 2022	0%
		Output: 	Wed Oct 19 08:18:04 2022	100%
PLINK PED/MAP to GDS Format:
Import 9088 variants from 'tmp.map'
Chromosome:
  1  10  11  12  13  14  15  16  17  18  19   2  20  21  22   3   4   5   6   7 
716 483 447 427 344 282 262 278 207 266 120 742 229 126 116 609 562 566 565 472 
  8   9   X 
488 416 365 
Reading 'tmp.ped'
Output: 'test.gds'
Import 279 samples
Transpose the genotypic matrix ...
Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (1.3M)
    # of fragments: 50
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (711.4K, reduced: 618.7K)
    # of fragments: 26
FUNCTION: snpgdsPairIBD
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,646 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
    # of samples: 93
    # of SNPs: 7,077
    using 1 thread
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 62.29%, 446/716
Chromosome 2: 62.67%, 465/742
Chromosome 3: 59.93%, 365/609
Chromosome 4: 64.23%, 361/562
Chromosome 5: 62.37%, 353/566
Chromosome 6: 59.82%, 338/565
Chromosome 7: 63.14%, 298/472
Chromosome 8: 57.58%, 281/488
Chromosome 9: 62.98%, 262/416
Chromosome 10: 60.46%, 292/483
Chromosome 11: 63.09%, 282/447
Chromosome 12: 62.76%, 268/427
Chromosome 13: 63.08%, 217/344
Chromosome 14: 63.83%, 180/282
Chromosome 15: 63.74%, 167/262
Chromosome 16: 62.23%, 173/278
Chromosome 17: 65.70%, 136/207
Chromosome 18: 59.40%, 158/266
Chromosome 19: 68.33%, 82/120
Chromosome 20: 66.38%, 152/229
Chromosome 21: 61.11%, 77/126
Chromosome 22: 57.76%, 67/116
5,420 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 25
    # of SNPs: 250
    using 1 thread
Specifying allele frequencies, mean: 0.486, sd: 0.284
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6112
MLE IBD:	Wed Oct 19 08:18:06 2022	0%
MLE IBD:	Wed Oct 19 08:18:06 2022	100%
IBD analysis (PLINK method of moment) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 25
    # of SNPs: 250
    using 1 thread
Specifying allele frequencies, mean: 0.486, sd: 0.284
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 6112
Wed Oct 19 08:18:06 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:06 2022    Done.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 25
    # of SNPs: 250
    using 1 thread
Specifying allele frequencies, mean: 0.486, sd: 0.284
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6112
MLE IBD:	Wed Oct 19 08:18:06 2022	0%
MLE IBD:	Wed Oct 19 08:18:07 2022	100%
Genotype matrix: 250 SNPs X 25 samples
[1] -370.7482
[1] -402.2141
[1] -383.7897
[1] -377.9084
[1] -381.3139
[1] -397.5581
[1] -378.3344
[1] -370.703
[1] -376.103
[1] -377.7911
[1] -375.5425
[1] -373.13
[1] -383.6992
[1] -393.5194
[1] -371.9843
[1] -369.6468
[1] -374.5139
[1] -377.841
[1] -387.5622
[1] -377.1646
[1] -377.4659
[1] -375.2204
[1] -372.0639
[1] -379.816
FUNCTION: snpgdsPairIBDMLELogLik
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,646 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
    # of samples: 93
    # of SNPs: 7,077
    using 1 thread
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 62.29%, 446/716
Chromosome 2: 62.67%, 465/742
Chromosome 3: 59.93%, 365/609
Chromosome 4: 64.23%, 361/562
Chromosome 5: 62.37%, 353/566
Chromosome 6: 59.82%, 338/565
Chromosome 7: 63.14%, 298/472
Chromosome 8: 57.58%, 281/488
Chromosome 9: 62.98%, 262/416
Chromosome 10: 60.46%, 292/483
Chromosome 11: 63.09%, 282/447
Chromosome 12: 62.76%, 268/427
Chromosome 13: 63.08%, 217/344
Chromosome 14: 63.83%, 180/282
Chromosome 15: 63.74%, 167/262
Chromosome 16: 62.23%, 173/278
Chromosome 17: 65.70%, 136/207
Chromosome 18: 59.40%, 158/266
Chromosome 19: 68.33%, 82/120
Chromosome 20: 66.38%, 152/229
Chromosome 21: 61.11%, 77/126
Chromosome 22: 57.76%, 67/116
5,420 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 25
    # of SNPs: 250
    using 1 thread
Specifying allele frequencies, mean: 0.486, sd: 0.284
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6112
MLE IBD:	Wed Oct 19 08:18:07 2022	0%
MLE IBD:	Wed Oct 19 08:18:08 2022	100%
IBD analysis (PLINK method of moment) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 25
    # of SNPs: 250
    using 1 thread
Specifying allele frequencies, mean: 0.486, sd: 0.284
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 6112
Wed Oct 19 08:18:08 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:08 2022    Done.
Genotype matrix: 250 SNPs X 25 samples
[1] -370.7482
[1] -402.2141
[1] -383.7897
[1] -377.9084
[1] -381.3139
[1] -397.5581
[1] -378.3344
[1] -370.703
[1] -376.103
[1] -377.7911
[1] -375.5425
[1] -373.13
[1] -383.6992
[1] -393.5194
[1] -371.9843
[1] -369.6468
[1] -374.5139
[1] -377.841
[1] -387.5622
[1] -377.1646
[1] -377.4659
[1] -375.2204
[1] -372.0639
[1] -379.816
FUNCTION: snpgdsPairScore
Excluding 365 SNPs on non-autosomes
Pair Score Calculation:
    # of samples: 120
    # of SNPs: 8,723
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
List of 3
 $ sample.id: chr [1:120] "NA19139" "NA19160" "NA07034" "NA12814" ...
 $ snp.id   : int [1:8723] 1 2 3 4 5 6 7 8 9 10 ...
 $ score    :'data.frame':	60 obs. of  5 variables:
  ..$ Avg    : num [1:60] 1.72 1.73 1.71 1.72 1.73 ...
  ..$ SD     : num [1:60] 0.452 0.443 0.457 0.45 0.443 ...
  ..$ Num    : int [1:60] 8684 8627 8669 8637 8682 8634 8654 8678 8680 8679 ...
  ..$ Sample1: chr [1:60] "NA19139" "NA10847" "NA18515" "NA19129" ...
  ..$ Sample2: chr [1:60] "NA19138" "NA12146" "NA18516" "NA19128" ...
Pair Score Calculation:
    # of samples: 120
    # of SNPs: 8,723
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
List of 3
 $ sample.id: chr [1:120] "NA19139" "NA19160" "NA07034" "NA12814" ...
 $ snp.id   : int [1:8723] 1 2 3 4 5 6 7 8 9 10 ...
 $ score    :'data.frame':	60 obs. of  5 variables:
  ..$ Avg    : num [1:60] 0.999 1 1 1 1 ...
  ..$ SD     : num [1:60] 0.024 0 0.0186 0.0215 0.0215 ...
  ..$ Num    : int [1:60] 8684 8627 8669 8637 8682 8634 8654 8678 8680 8679 ...
  ..$ Sample1: chr [1:60] "NA19139" "NA10847" "NA18515" "NA19129" ...
  ..$ Sample2: chr [1:60] "NA19138" "NA12146" "NA18516" "NA19128" ...
Pair Score Calculation:
    # of samples: 120
    # of SNPs: 8,723
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
List of 3
 $ sample.id: chr [1:120] "NA19139" "NA19160" "NA07034" "NA12814" ...
 $ snp.id   : int [1:8723] 1 2 3 4 5 6 7 8 9 10 ...
 $ score    : num [1:3, 1:8723] 1.75 0.437 60 1.583 0.497 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:3] "Avg" "SD" "Num"
  .. ..$ : NULL
Pair Score Calculation:
    # of samples: 120
    # of SNPs: 8,723
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
List of 3
 $ sample.id: chr [1:120] "NA19139" "NA19160" "NA07034" "NA12814" ...
 $ snp.id   : int [1:8723] 1 2 3 4 5 6 7 8 9 10 ...
 $ score    : int [1:60, 1:8723] 1 1 2 2 2 2 2 1 2 2 ...
Pair Score Calculation:
    # of samples: 120
    # of SNPs: 8,723
Method: IBS
Output: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/tmp.gds
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
FUNCTION: snpgdsSNPList
FUNCTION: snpgdsSNPListClass
FUNCTION: snpgdsSNPListIntersect
FUNCTION: snpgdsSNPRateFreq
FUNCTION: snpgdsSampMissRate
FUNCTION: snpgdsSelectSNP
Excluding 365 SNPs on non-autosomes
Excluding 1,221 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.95)
FUNCTION: snpgdsSlidingWindow
Sliding Window Analysis:
Excluding 8 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
    # of samples: 279
    # of SNPs: 9,080
    using 1 thread
    window size: 500000, shift: 100000 (basepair)
Chromosome Set: 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23
Wed Oct 19 08:18:09 2022, Chromosome 1 (716 SNPs), 2448 windows
Wed Oct 19 08:18:09 2022, Chromosome 2 (742 SNPs), 2416 windows
Wed Oct 19 08:18:09 2022, Chromosome 3 (609 SNPs), 1985 windows
Wed Oct 19 08:18:09 2022, Chromosome 4 (562 SNPs), 1894 windows
Wed Oct 19 08:18:09 2022, Chromosome 5 (566 SNPs), 1797 windows
Wed Oct 19 08:18:10 2022, Chromosome 6 (565 SNPs), 1694 windows
Wed Oct 19 08:18:10 2022, Chromosome 7 (472 SNPs), 1573 windows
Wed Oct 19 08:18:10 2022, Chromosome 8 (488 SNPs), 1445 windows
Wed Oct 19 08:18:10 2022, Chromosome 9 (416 SNPs), 1393 windows
Wed Oct 19 08:18:10 2022, Chromosome 10 (483 SNPs), 1343 windows
Wed Oct 19 08:18:10 2022, Chromosome 11 (447 SNPs), 1338 windows
Wed Oct 19 08:18:10 2022, Chromosome 12 (427 SNPs), 1316 windows
Wed Oct 19 08:18:10 2022, Chromosome 13 (344 SNPs), 948 windows
Wed Oct 19 08:18:10 2022, Chromosome 14 (281 SNPs), 847 windows
Wed Oct 19 08:18:10 2022, Chromosome 15 (262 SNPs), 774 windows
Wed Oct 19 08:18:10 2022, Chromosome 16 (278 SNPs), 873 windows
Wed Oct 19 08:18:10 2022, Chromosome 17 (207 SNPs), 773 windows
Wed Oct 19 08:18:10 2022, Chromosome 18 (266 SNPs), 753 windows
Wed Oct 19 08:18:10 2022, Chromosome 19 (120 SNPs), 627 windows
Wed Oct 19 08:18:10 2022, Chromosome 20 (229 SNPs), 602 windows
Wed Oct 19 08:18:10 2022, Chromosome 21 (126 SNPs), 311 windows
Wed Oct 19 08:18:10 2022, Chromosome 22 (116 SNPs), 312 windows
Wed Oct 19 08:18:10 2022, Chromosome 23 (358 SNPs), 1507 windows
Wed Oct 19 08:18:11 2022 	Done.
FUNCTION: snpgdsSummary
The file name: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/hapmap_geno.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
FUNCTION: snpgdsTranspose
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
SNP genotypes: 279 samples, 9088 SNPs
Genotype matrix is being transposed ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (1.3M)
    # of fragments: 28
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (709.6K, reduced: 619.1K)
    # of fragments: 26
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in individual-major mode (SNP X Sample).
FUNCTION: snpgdsVCF2GDS
##fileformat=VCFv4.1
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	NA00001	NA00002	NA00003
20	14370	rs6054257	G	A	29	PASS	NS=3;DP=14;AF=0.5;DB;H2	GT:GQ:DP:HQ	0|0:48:1:51,51	1|0:48:8:51,51	1/1:43:5:.,.
20	17330	.	T	A	3	q10	NS=3;DP=11;AF=0.017	GT:GQ:DP:HQ	0|0:49:3:58,50	0|1:3:5:65,3	0/0:41:3
20	1110696	rs6040355	A	G,T	67	PASS	NS=2;DP=10;AF=0.333,0.667;AA=T;DB	GT:GQ:DP:HQ	1|2:21:6:23,27	2|1:2:0:18,2	2/2:35:4
20	1230237	.	T	.	47	PASS	NS=3;DP=13;AA=T	GT:GQ:DP:HQ	0|0:54:7:56,60	0|0:48:4:51,51	0/0:61:2
20	1234567	microsat1	GTC	G,GTCT	50	PASS	NS=3;DP=9;AA=G	GT:GQ:DP	0/1:35:4	0/2:17:2	1/1:40:3
Start file conversion from VCF to SNP GDS ...
Method: extracting biallelic SNPs
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 2 variants.
+ genotype   { Bit2 3x2, 2B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test1.gds' (2.9K)
    # of fragments: 46
    save to 'test1.gds.tmp'
    rename 'test1.gds.tmp' (2.6K, reduced: 312B)
    # of fragments: 20
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test1.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Start file conversion from VCF to SNP GDS ...
Method: extracting biallelic SNPs
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 2 variants.
+ genotype   { Bit2 3x2, 2B } *
SNP genotypes: 3 samples, 2 SNPs
Genotype matrix is being transposed ...
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test2.gds' (3.0K)
    # of fragments: 48
    save to 'test2.gds.tmp'
    rename 'test2.gds.tmp' (2.6K, reduced: 417B)
    # of fragments: 20
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test2.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in individual-major mode (SNP X Sample).
Start file conversion from VCF to SNP GDS ...
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
SNP genotypes: 3 samples, 5 SNPs
Genotype matrix is being transposed ...
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test3.gds' (3.1K)
    # of fragments: 48
    save to 'test3.gds.tmp'
    rename 'test3.gds.tmp' (2.7K, reduced: 419B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test3.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in individual-major mode (SNP X Sample).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
Start file conversion from VCF to SNP GDS ...
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test4.gds' (3.0K)
    # of fragments: 46
    save to 'test4.gds.tmp'
    rename 'test4.gds.tmp' (2.7K, reduced: 312B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test4.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
Start file conversion from VCF to SNP GDS ...
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test5.gds' (3.0K)
    # of fragments: 46
    save to 'test5.gds.tmp'
    rename 'test5.gds.tmp' (2.7K, reduced: 312B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., T/A,G).
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test5.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
FUNCTION: snpgdsVCF2GDS_R
##fileformat=VCFv4.1
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	NA00001	NA00002	NA00003
20	14370	rs6054257	G	A	29	PASS	NS=3;DP=14;AF=0.5;DB;H2	GT:GQ:DP:HQ	0|0:48:1:51,51	1|0:48:8:51,51	1/1:43:5:.,.
20	17330	.	T	A	3	q10	NS=3;DP=11;AF=0.017	GT:GQ:DP:HQ	0|0:49:3:58,50	0|1:3:5:65,3	0/0:41:3
20	1110696	rs6040355	A	G,T	67	PASS	NS=2;DP=10;AF=0.333,0.667;AA=T;DB	GT:GQ:DP:HQ	1|2:21:6:23,27	2|1:2:0:18,2	2/2:35:4
20	1230237	.	T	.	47	PASS	NS=3;DP=13;AA=T	GT:GQ:DP:HQ	0|0:54:7:56,60	0|0:48:4:51,51	0/0:61:2
20	1234567	microsat1	GTC	G,GTCT	50	PASS	NS=3;DP=9;AA=G	GT:GQ:DP	0/1:35:4	0/2:17:2	1/1:40:3
Start snpgdsVCF2GDS ...
	Extracting bi-allelic and polymorhpic SNPs.
	Scanning ...
	file: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Wed Oct 19 08:18:12 2022 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 2 SNPs ...
	file: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf
[1] 1
Wed Oct 19 08:18:12 2022 	Done.
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test1.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Start snpgdsVCF2GDS ...
	Extracting bi-allelic and polymorhpic SNPs.
	Scanning ...
	file: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Wed Oct 19 08:18:12 2022 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 2 SNPs ...
	file: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf
[1] 1
Wed Oct 19 08:18:12 2022 	Done.
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test2.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Start snpgdsVCF2GDS ...
	Storing dosage of the reference allele for all variant sites, including bi-allelic SNPs, multi-allelic SNPs, indels and structural variants.
	Scanning ...
	file: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Wed Oct 19 08:18:12 2022 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 5 SNPs ...
	file: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf
Wed Oct 19 08:18:12 2022 	Done.
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test3.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
Start snpgdsVCF2GDS ...
	Storing dosage of the reference allele for all variant sites, including bi-allelic SNPs, multi-allelic SNPs, indels and structural variants.
	Scanning ...
	file: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Wed Oct 19 08:18:12 2022 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 5 SNPs ...
	file: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/SNPRelate/extdata/sequence.vcf
Wed Oct 19 08:18:12 2022 	Done.
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.15-bioc/meat/SNPRelate.Rcheck/tests/test4.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
SNP Correlation:
    # of samples: 90
    # of SNPs: 9,088
    using 1 thread
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Wed Oct 19 08:18:14 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:14 2022    Done.
SNP Correlation:
    # of samples: 90
    # of SNPs: 9,088
    using 1 thread
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Wed Oct 19 08:18:14 2022

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:14 2022    Done.
SNP Loading:
    # of samples: 90
    # of SNPs: 8,695
    using 1 thread
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 787449
Wed Oct 19 08:18:14 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:14 2022    Done.
Sample Loading:
    # of samples: 100
    # of SNPs: 8,695
    using 1 thread
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 875255
Wed Oct 19 08:18:14 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:14 2022    Done.
SNP Correlation:
    # of samples: 90
    # of SNPs: 9,088
    using 2 threads
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Wed Oct 19 08:18:14 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:14 2022    Done.
SNP Correlation:
    # of samples: 90
    # of SNPs: 9,088
    using 2 threads
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Wed Oct 19 08:18:14 2022

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:14 2022    Done.
SNP Loading:
    # of samples: 90
    # of SNPs: 8,695
    using 1 thread
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 787449
Wed Oct 19 08:18:14 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:14 2022    Done.
Sample Loading:
    # of samples: 100
    # of SNPs: 8,695
    using 1 thread
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 875255
Wed Oct 19 08:18:14 2022    (internal increment: 65536)

[..................................................]  0%, ETC: ---        
[==================================================] 100%, completed, 0s
Wed Oct 19 08:18:14 2022    Done.


RUNIT TEST PROTOCOL -- Wed Oct 19 08:18:14 2022 
*********************************************** 
Number of test functions: 13 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
SNPRelate RUnit Tests - 13 test functions, 0 errors, 0 failures
Number of test functions: 13 
Number of errors: 0 
Number of failures: 0 
> 
> proc.time()
   user  system elapsed 
 56.327   3.052  59.173

name	user	system	elapsed
SNPGDSFileClass-class	0.059	0.003	0.062
SNPRelate-package	1.855	0.130	1.997
snpgdsAdmixPlot	0.832	0.013	0.848
snpgdsAdmixProp	0.775	0.012	0.787
snpgdsAlleleSwitch	0.143	0.009	0.153
snpgdsApartSelection	0.227	0.022	0.250
snpgdsBED2GDS	0.187	0.029	0.216
snpgdsClose	0.042	0.001	0.044
snpgdsCombineGeno	0.174	0.040	0.215
snpgdsCreateGeno	0.763	0.020	0.784
snpgdsCreateGenoSet	0.252	0.020	0.273
snpgdsCutTree	3.219	0.133	3.362
snpgdsDiss	2.519	0.014	2.538
snpgdsDrawTree	2.113	0.011	2.127
snpgdsEIGMIX	0.745	0.009	0.755
snpgdsErrMsg	0.000	0.000	0.001
snpgdsExampleFileName	0.001	0.000	0.001
snpgdsFst	0.053	0.004	0.057
snpgdsGDS2BED	0.113	0.012	0.126
snpgdsGDS2Eigen	0.878	0.076	0.956
snpgdsGDS2PED	0.620	0.045	0.670
snpgdsGEN2GDS	0.000	0.001	0.000
snpgdsGRM	1.742	0.035	1.781
snpgdsGetGeno	0.098	0.021	0.119
snpgdsHCluster	2.550	0.036	2.590
snpgdsHWE	0.027	0.003	0.030
snpgdsIBDKING	3.074	0.082	3.159
snpgdsIBDMLE	0.883	0.013	0.899
snpgdsIBDMLELogLik	0.960	0.019	0.982
snpgdsIBDMoM	0.467	0.031	0.501
snpgdsIBDSelection	0.160	0.012	0.173
snpgdsIBS	0.403	0.010	0.413
snpgdsIBSNum	0.516	0.021	0.539
snpgdsIndInb	0.048	0.003	0.051
snpgdsIndInbCoef	0.010	0.002	0.012
snpgdsIndivBeta	0.293	0.005	0.298
snpgdsLDMat	0.389	0.019	0.410
snpgdsLDpair	0.004	0.001	0.006
snpgdsLDpruning	0.279	0.011	0.290
snpgdsMergeGRM	2.984	0.078	3.067
snpgdsOpen	0.042	0.002	0.044
snpgdsOption	0.003	0.001	0.004
snpgdsPCA	0.927	0.019	0.949
snpgdsPCACorr	0.972	0.030	1.005
snpgdsPCASNPLoading	0.962	0.012	0.976
snpgdsPCASampLoading	0.766	0.008	0.775
snpgdsPED2GDS	1.874	0.114	1.997
snpgdsPairIBD	1.442	0.019	1.464
snpgdsPairIBDMLELogLik	0.755	0.023	0.778
snpgdsPairScore	0.401	0.121	0.524
snpgdsSNPList	0.013	0.002	0.014
snpgdsSNPListIntersect	0.090	0.004	0.093
snpgdsSNPRateFreq	0.202	0.005	0.208
snpgdsSampMissRate	0.010	0.001	0.011
snpgdsSelectSNP	0.010	0.001	0.012
snpgdsSlidingWindow	1.686	0.155	1.842
snpgdsSummary	0.089	0.001	0.090
snpgdsTranspose	0.224	0.011	0.237
snpgdsVCF2GDS	0.438	0.305	0.745
snpgdsVCF2GDS_R	0.196	0.149	0.348

CHECK results for SNPRelate on merida1

Summary

Command output

Installation output

Tests output

Example timings