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This page was generated on 2025-01-02 15:42 -0500 (Thu, 02 Jan 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
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nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.2 (2024-10-31) -- "Pile of Leaves" | 4744 |
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 379/431 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | ||||||||
spatialLIBD 1.18.0 (landing page) Leonardo Collado-Torres
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | ||||||||
To the developers/maintainers of the spatialLIBD package: - 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: spatialLIBD |
Version: 1.18.0 |
Command: /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:spatialLIBD.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings spatialLIBD_1.18.0.tar.gz |
StartedAt: 2025-01-02 12:39:40 -0500 (Thu, 02 Jan 2025) |
EndedAt: 2025-01-02 12:57:21 -0500 (Thu, 02 Jan 2025) |
EllapsedTime: 1060.9 seconds |
RetCode: 0 |
Status: OK |
CheckDir: spatialLIBD.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD check --install=check:spatialLIBD.install-out.txt --library=/home/biocbuild/bbs-3.20-bioc/R/site-library --timings spatialLIBD_1.18.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.20-data-experiment/meat/spatialLIBD.Rcheck’ * using R version 4.4.2 (2024-10-31) * using platform: x86_64-pc-linux-gnu * R was compiled by gcc (Ubuntu 13.2.0-23ubuntu4) 13.2.0 GNU Fortran (Ubuntu 13.2.0-23ubuntu4) 13.2.0 * running under: Ubuntu 24.04.1 LTS * using session charset: UTF-8 * checking for file ‘spatialLIBD/DESCRIPTION’ ... OK * this is package ‘spatialLIBD’ version ‘1.18.0’ * 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 ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘spatialLIBD’ 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 loading without being on the library search path ... 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 LazyData ... OK * checking data for ASCII and uncompressed saves ... OK * checking files in ‘vignettes’ ... OK * checking examples ... OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed vis_gene 24.596 2.447 27.417 vis_clus 18.722 2.717 21.796 add_images 18.870 1.999 23.253 img_update_all 18.509 1.534 20.066 cluster_import 15.798 2.648 18.814 vis_grid_gene 15.811 2.494 18.670 cluster_export 15.394 2.604 18.361 vis_grid_clus 15.288 2.125 17.769 add_qc_metrics 14.940 2.105 17.238 add_key 15.181 1.668 17.218 vis_clus_p 14.597 1.861 16.972 frame_limits 14.040 2.257 17.489 geom_spatial 14.220 1.916 16.494 img_edit 14.137 1.921 16.388 check_spe 14.282 1.727 16.464 vis_gene_p 14.411 1.251 16.121 img_update 14.044 1.582 16.090 sce_to_spe 13.730 1.244 15.453 * 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 re-building of vignette outputs ... OK * checking PDF version of manual ... OK * DONE Status: OK
spatialLIBD.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD INSTALL spatialLIBD ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.20-bioc/R/site-library’ * installing *source* package ‘spatialLIBD’ ... ** using staged installation ** R ** data *** moving datasets to lazyload DB ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices *** copying figures ** 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 (spatialLIBD)
spatialLIBD.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: x86_64-pc-linux-gnu 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(spatialLIBD) Loading required package: SpatialExperiment Loading required package: SingleCellExperiment Loading required package: SummarizedExperiment Loading required package: MatrixGenerics Loading required package: matrixStats Attaching package: 'MatrixGenerics' The following objects are masked from 'package:matrixStats': colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse, colCounts, colCummaxs, colCummins, colCumprods, colCumsums, colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs, colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats, colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds, colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads, colWeightedMeans, colWeightedMedians, colWeightedSds, colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet, rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods, rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps, rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins, rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks, rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars, rowWeightedMads, rowWeightedMeans, rowWeightedMedians, rowWeightedSds, rowWeightedVars Loading required package: GenomicRanges Loading required package: stats4 Loading required package: BiocGenerics Attaching package: 'BiocGenerics' The following objects are masked from 'package:stats': IQR, mad, sd, var, xtabs The following objects are masked from 'package:base': Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append, as.data.frame, basename, cbind, colnames, dirname, do.call, duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted, lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind, rownames, sapply, saveRDS, setdiff, table, tapply, union, unique, unsplit, which.max, which.min Loading required package: S4Vectors Attaching package: 'S4Vectors' The following object is masked from 'package:utils': findMatches The following objects are masked from 'package:base': I, expand.grid, unname Loading required package: IRanges Loading required package: GenomeInfoDb Loading required package: Biobase Welcome to Bioconductor Vignettes contain introductory material; view with 'browseVignettes()'. To cite Bioconductor, see 'citation("Biobase")', and for packages 'citation("pkgname")'. Attaching package: 'Biobase' The following object is masked from 'package:MatrixGenerics': rowMedians The following objects are masked from 'package:matrixStats': anyMissing, rowMedians > > test_check("spatialLIBD") rgstr_> ## Ensure reproducibility of example data rgstr_> set.seed(20220907) rgstr_> ## Generate example data rgstr_> sce <- scuttle::mockSCE() rgstr_> ## Add some sample IDs rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE) rgstr_> ## Add a sample-level covariate: age rgstr_> ages <- rnorm(5, mean = 20, sd = 4) rgstr_> names(ages) <- LETTERS[1:5] rgstr_> sce$age <- ages[sce$sample_id] rgstr_> ## Add gene-level information rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce))) rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce))) rgstr_> ## Pseudo-bulk rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL) rgstr_> colData(sce_pseudo) DataFrame with 20 rows and 8 columns Mutation_Status Cell_Cycle Treatment sample_id age <character> <character> <character> <character> <numeric> A_G0 NA G0 NA A 19.1872 B_G0 NA G0 NA B 25.3496 C_G0 NA G0 NA C 24.1802 D_G0 NA G0 NA D 15.5211 E_G0 NA G0 NA E 20.9701 ... ... ... ... ... ... A_S NA S NA A 19.1872 B_S NA S NA B 25.3496 C_S NA S NA C 24.1802 D_S NA S NA D 15.5211 E_S NA S NA E 20.9701 registration_variable registration_sample_id ncells <character> <character> <integer> A_G0 G0 A 8 B_G0 G0 B 13 C_G0 G0 C 9 D_G0 G0 D 7 E_G0 G0 E 10 ... ... ... ... A_S S A 12 B_S S B 8 C_S S C 7 D_S S D 14 E_S S E 11 rgstr_> ## Ensure reproducibility of example data rgstr_> set.seed(20220907) rgstr_> ## Generate example data rgstr_> sce <- scuttle::mockSCE() rgstr_> ## Add some sample IDs rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE) rgstr_> ## Add a sample-level covariate: age rgstr_> ages <- rnorm(5, mean = 20, sd = 4) rgstr_> names(ages) <- LETTERS[1:5] rgstr_> sce$age <- ages[sce$sample_id] rgstr_> ## Add gene-level information rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce))) rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce))) rgstr_> ## Pseudo-bulk rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL) rgstr_> colData(sce_pseudo) DataFrame with 20 rows and 8 columns Mutation_Status Cell_Cycle Treatment sample_id age <character> <character> <character> <character> <numeric> A_G0 NA G0 NA A 19.1872 B_G0 NA G0 NA B 25.3496 C_G0 NA G0 NA C 24.1802 D_G0 NA G0 NA D 15.5211 E_G0 NA G0 NA E 20.9701 ... ... ... ... ... ... A_S NA S NA A 19.1872 B_S NA S NA B 25.3496 C_S NA S NA C 24.1802 D_S NA S NA D 15.5211 E_S NA S NA E 20.9701 registration_variable registration_sample_id ncells <character> <character> <integer> A_G0 G0 A 8 B_G0 G0 B 13 C_G0 G0 C 9 D_G0 G0 D 7 E_G0 G0 E 10 ... ... ... ... A_S S A 12 B_S S B 8 C_S S C 7 D_S S D 14 E_S S E 11 rgst__> example("registration_model", package = "spatialLIBD") rgstr_> example("registration_pseudobulk", package = "spatialLIBD") rgstr_> ## Ensure reproducibility of example data rgstr_> set.seed(20220907) rgstr_> ## Generate example data rgstr_> sce <- scuttle::mockSCE() rgstr_> ## Add some sample IDs rgstr_> sce$sample_id <- sample(LETTERS[1:5], ncol(sce), replace = TRUE) rgstr_> ## Add a sample-level covariate: age rgstr_> ages <- rnorm(5, mean = 20, sd = 4) rgstr_> names(ages) <- LETTERS[1:5] rgstr_> sce$age <- ages[sce$sample_id] rgstr_> ## Add gene-level information rgstr_> rowData(sce)$ensembl <- paste0("ENSG", seq_len(nrow(sce))) rgstr_> rowData(sce)$gene_name <- paste0("gene", seq_len(nrow(sce))) rgstr_> ## Pseudo-bulk rgstr_> sce_pseudo <- registration_pseudobulk(sce, "Cell_Cycle", "sample_id", c("age"), min_ncells = NULL) rgstr_> colData(sce_pseudo) DataFrame with 20 rows and 8 columns Mutation_Status Cell_Cycle Treatment sample_id age <character> <character> <character> <character> <numeric> A_G0 NA G0 NA A 19.1872 B_G0 NA G0 NA B 25.3496 C_G0 NA G0 NA C 24.1802 D_G0 NA G0 NA D 15.5211 E_G0 NA G0 NA E 20.9701 ... ... ... ... ... ... A_S NA S NA A 19.1872 B_S NA S NA B 25.3496 C_S NA S NA C 24.1802 D_S NA S NA D 15.5211 E_S NA S NA E 20.9701 registration_variable registration_sample_id ncells <character> <character> <integer> A_G0 G0 A 8 B_G0 G0 B 13 C_G0 G0 C 9 D_G0 G0 D 7 E_G0 G0 E 10 ... ... ... ... A_S S A 12 B_S S B 8 C_S S C 7 D_S S D 14 E_S S E 11 rgstr_> registration_mod <- registration_model(sce_pseudo, "age") rgstr_> head(registration_mod) registration_variableG0 registration_variableG1 registration_variableG2M A_G0 1 0 0 B_G0 1 0 0 C_G0 1 0 0 D_G0 1 0 0 E_G0 1 0 0 A_G1 0 1 0 registration_variableS age A_G0 0 19.18719 B_G0 0 25.34965 C_G0 0 24.18019 D_G0 0 15.52107 E_G0 0 20.97006 A_G1 0 19.18719 rgst__> block_cor <- registration_block_cor(sce_pseudo, registration_mod) [ FAIL 0 | WARN 0 | SKIP 0 | PASS 33 ] > > proc.time() user system elapsed 87.968 6.797 96.541
spatialLIBD.Rcheck/spatialLIBD-Ex.timings
name | user | system | elapsed | |
add10xVisiumAnalysis | 0 | 0 | 0 | |
add_images | 18.870 | 1.999 | 23.253 | |
add_key | 15.181 | 1.668 | 17.218 | |
add_qc_metrics | 14.940 | 2.105 | 17.238 | |
annotate_registered_clusters | 1.137 | 0.034 | 1.335 | |
check_modeling_results | 1.201 | 0.078 | 1.440 | |
check_sce | 3.346 | 0.328 | 3.839 | |
check_sce_layer | 1.256 | 0.111 | 1.623 | |
check_spe | 14.282 | 1.727 | 16.464 | |
cluster_export | 15.394 | 2.604 | 18.361 | |
cluster_import | 15.798 | 2.648 | 18.814 | |
enough_ram | 0.007 | 0.003 | 0.010 | |
fetch_data | 1.269 | 0.238 | 1.667 | |
frame_limits | 14.040 | 2.257 | 17.489 | |
gene_set_enrichment | 1.316 | 0.113 | 1.618 | |
gene_set_enrichment_plot | 1.465 | 0.172 | 1.801 | |
geom_spatial | 14.220 | 1.916 | 16.494 | |
get_colors | 1.211 | 0.095 | 1.471 | |
img_edit | 14.137 | 1.921 | 16.388 | |
img_update | 14.044 | 1.582 | 16.090 | |
img_update_all | 18.509 | 1.534 | 20.066 | |
layer_boxplot | 3.288 | 0.177 | 3.788 | |
layer_matrix_plot | 0.010 | 0.001 | 0.010 | |
layer_stat_cor | 1.112 | 0.047 | 1.319 | |
layer_stat_cor_plot | 1.207 | 0.038 | 1.404 | |
locate_images | 0 | 0 | 0 | |
read10xVisiumAnalysis | 0 | 0 | 0 | |
read10xVisiumWrapper | 0 | 0 | 0 | |
registration_block_cor | 3.798 | 0.335 | 4.134 | |
registration_model | 0.636 | 0.003 | 0.640 | |
registration_pseudobulk | 0.595 | 0.002 | 0.598 | |
registration_stats_anova | 2.713 | 0.017 | 2.731 | |
registration_stats_enrichment | 2.905 | 0.017 | 2.921 | |
registration_stats_pairwise | 2.731 | 0.007 | 2.739 | |
registration_wrapper | 4.111 | 0.016 | 4.127 | |
run_app | 0.001 | 0.000 | 0.000 | |
sce_to_spe | 13.730 | 1.244 | 15.453 | |
sig_genes_extract | 3.258 | 0.204 | 3.786 | |
sig_genes_extract_all | 3.293 | 0.305 | 3.921 | |
sort_clusters | 0.008 | 0.001 | 0.009 | |
vis_clus | 18.722 | 2.717 | 21.796 | |
vis_clus_p | 14.597 | 1.861 | 16.972 | |
vis_gene | 24.596 | 2.447 | 27.417 | |
vis_gene_p | 14.411 | 1.251 | 16.121 | |
vis_grid_clus | 15.288 | 2.125 | 17.769 | |
vis_grid_gene | 15.811 | 2.494 | 18.670 | |