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This page was generated on 2024-05-02 14:51:34 -0400 (Thu, 02 May 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4753 |
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 378/430 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | ||||||||
spatialLIBD 1.16.0 (landing page) Leonardo Collado-Torres
| nebbiolo1 | Linux (Ubuntu 22.04.3 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: 1.16.0 |
Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:spatialLIBD.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings spatialLIBD_1.16.0.tar.gz |
StartedAt: 2024-05-02 12:37:29 -0400 (Thu, 02 May 2024) |
EndedAt: 2024-05-02 12:58:00 -0400 (Thu, 02 May 2024) |
EllapsedTime: 1231.3 seconds |
RetCode: 0 |
Status: OK |
CheckDir: spatialLIBD.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:spatialLIBD.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings spatialLIBD_1.16.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.19-data-experiment/meat/spatialLIBD.Rcheck’ * using R version 4.4.0 beta (2024-04-15 r86425) * using platform: x86_64-pc-linux-gnu * R was compiled by gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 * running under: Ubuntu 22.04.4 LTS * using session charset: UTF-8 * checking for file ‘spatialLIBD/DESCRIPTION’ ... OK * this is package ‘spatialLIBD’ version ‘1.16.0’ * 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 43.237 4.244 48.096 vis_clus 31.810 3.600 36.022 add_images 28.598 2.284 33.755 img_update_all 27.058 2.487 29.833 vis_grid_gene 26.176 2.470 29.329 vis_grid_clus 25.736 2.457 29.061 geom_spatial 24.583 2.394 27.564 vis_clus_p 24.329 2.355 27.397 add_key 24.337 2.263 27.258 img_edit 23.789 2.671 26.944 cluster_import 24.407 2.018 26.984 vis_gene_p 24.143 2.196 27.105 check_spe 24.019 2.120 26.797 cluster_export 23.130 1.886 25.723 img_update 22.632 2.254 25.451 frame_limits 22.521 2.169 25.316 sce_to_spe 22.506 1.928 25.746 * 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-3.19-bioc/R/bin/R CMD INSTALL spatialLIBD ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.19-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 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" 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, 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 23 ] > > proc.time() user system elapsed 54.098 4.745 59.763
spatialLIBD.Rcheck/spatialLIBD-Ex.timings
name | user | system | elapsed | |
add10xVisiumAnalysis | 0.000 | 0.000 | 0.001 | |
add_images | 28.598 | 2.284 | 33.755 | |
add_key | 24.337 | 2.263 | 27.258 | |
annotate_registered_clusters | 1.200 | 0.170 | 1.616 | |
check_modeling_results | 1.231 | 0.197 | 1.605 | |
check_sce | 3.405 | 0.155 | 3.740 | |
check_sce_layer | 1.277 | 0.180 | 1.661 | |
check_spe | 24.019 | 2.120 | 26.797 | |
cluster_export | 23.130 | 1.886 | 25.723 | |
cluster_import | 24.407 | 2.018 | 26.984 | |
enough_ram | 0.007 | 0.002 | 0.009 | |
fetch_data | 1.331 | 0.228 | 1.767 | |
frame_limits | 22.521 | 2.169 | 25.316 | |
gene_set_enrichment | 1.377 | 0.147 | 1.761 | |
gene_set_enrichment_plot | 1.534 | 0.153 | 1.863 | |
geom_spatial | 24.583 | 2.394 | 27.564 | |
get_colors | 1.274 | 0.156 | 1.674 | |
img_edit | 23.789 | 2.671 | 26.944 | |
img_update | 22.632 | 2.254 | 25.451 | |
img_update_all | 27.058 | 2.487 | 29.833 | |
layer_boxplot | 3.156 | 0.408 | 3.948 | |
layer_matrix_plot | 0.011 | 0.000 | 0.011 | |
layer_stat_cor | 1.379 | 0.180 | 1.737 | |
layer_stat_cor_plot | 1.253 | 0.112 | 1.587 | |
locate_images | 0 | 0 | 0 | |
read10xVisiumAnalysis | 0.000 | 0.000 | 0.001 | |
read10xVisiumWrapper | 0 | 0 | 0 | |
registration_block_cor | 4.265 | 0.564 | 4.830 | |
registration_model | 0.921 | 0.064 | 0.984 | |
registration_pseudobulk | 0.858 | 0.040 | 0.898 | |
registration_stats_anova | 3.075 | 0.144 | 3.218 | |
registration_stats_enrichment | 3.235 | 0.152 | 3.387 | |
registration_stats_pairwise | 3.063 | 0.084 | 3.147 | |
registration_wrapper | 4.391 | 0.104 | 4.495 | |
run_app | 0.000 | 0.001 | 0.001 | |
sce_to_spe | 22.506 | 1.928 | 25.746 | |
sig_genes_extract | 2.773 | 0.852 | 4.016 | |
sig_genes_extract_all | 3.124 | 0.339 | 3.833 | |
sort_clusters | 0.004 | 0.000 | 0.004 | |
vis_clus | 31.810 | 3.600 | 36.022 | |
vis_clus_p | 24.329 | 2.355 | 27.397 | |
vis_gene | 43.237 | 4.244 | 48.096 | |
vis_gene_p | 24.143 | 2.196 | 27.105 | |
vis_grid_clus | 25.736 | 2.457 | 29.061 | |
vis_grid_gene | 26.176 | 2.470 | 29.329 | |