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This page was generated on 2024-04-16 14:51:29 -0400 (Tue, 16 Apr 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4676 |
| 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 379/429 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | ||||||||
| spatialLIBD 1.14.1 (landing page) Leonardo Collado-Torres
| nebbiolo2 | 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: 1.14.1 |
| Command: /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:spatialLIBD.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings spatialLIBD_1.14.1.tar.gz |
| StartedAt: 2024-04-16 12:22:50 -0400 (Tue, 16 Apr 2024) |
| EndedAt: 2024-04-16 12:45:43 -0400 (Tue, 16 Apr 2024) |
| EllapsedTime: 1372.5 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: spatialLIBD.Rcheck |
| Warnings: 0 |
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###
### Running command:
###
### /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:spatialLIBD.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings spatialLIBD_1.14.1.tar.gz
###
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##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.18-data-experiment/meat/spatialLIBD.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: x86_64-pc-linux-gnu (64-bit)
* 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 ‘1.14.1’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... 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 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 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 35.402 2.814 38.843
vis_clus 31.831 3.073 35.748
add_images 28.035 2.646 32.584
img_update_all 27.662 1.910 30.487
vis_grid_gene 25.656 2.437 28.697
vis_grid_clus 25.153 2.168 27.888
check_spe 24.863 2.260 27.639
vis_clus_p 25.057 2.021 28.380
vis_gene_p 24.956 1.807 27.393
cluster_import 24.406 1.916 26.874
add_key 23.428 2.084 26.073
cluster_export 23.443 1.900 25.972
geom_spatial 23.308 1.440 25.325
img_update 22.754 1.844 25.275
sce_to_spe 22.531 2.043 25.250
img_edit 22.929 1.268 24.708
frame_limits 22.513 1.271 24.375
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘testthat.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
‘TenX_data_download.Rmd’ using ‘UTF-8’... OK
‘guide_to_spatial_registration.Rmd’ using ‘UTF-8’... OK
‘spatialLIBD.Rmd’ using ‘UTF-8’... OK
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-3.18-bioc/R/bin/R CMD INSTALL spatialLIBD ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.18-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 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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.
> 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, sort, 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 12 ]
>
> proc.time()
user system elapsed
25.253 1.560 27.136
spatialLIBD.Rcheck/spatialLIBD-Ex.timings
| name | user | system | elapsed | |
| add10xVisiumAnalysis | 0 | 0 | 0 | |
| add_images | 28.035 | 2.646 | 32.584 | |
| add_key | 23.428 | 2.084 | 26.073 | |
| annotate_registered_clusters | 1.229 | 0.072 | 1.549 | |
| check_modeling_results | 1.169 | 0.069 | 1.425 | |
| check_sce | 3.426 | 0.130 | 3.762 | |
| check_sce_layer | 1.290 | 0.136 | 1.607 | |
| check_spe | 24.863 | 2.260 | 27.639 | |
| cluster_export | 23.443 | 1.900 | 25.972 | |
| cluster_import | 24.406 | 1.916 | 26.874 | |
| enough_ram | 0.004 | 0.004 | 0.007 | |
| fetch_data | 1.389 | 0.084 | 2.499 | |
| frame_limits | 22.513 | 1.271 | 24.375 | |
| gene_set_enrichment | 1.353 | 0.096 | 1.711 | |
| gene_set_enrichment_plot | 1.460 | 0.044 | 1.684 | |
| geom_spatial | 23.308 | 1.440 | 25.325 | |
| get_colors | 1.335 | 0.072 | 1.643 | |
| img_edit | 22.929 | 1.268 | 24.708 | |
| img_update | 22.754 | 1.844 | 25.275 | |
| img_update_all | 27.662 | 1.910 | 30.487 | |
| layer_boxplot | 3.295 | 0.276 | 3.988 | |
| layer_matrix_plot | 0.01 | 0.00 | 0.01 | |
| layer_stat_cor | 1.062 | 0.020 | 1.299 | |
| layer_stat_cor_plot | 1.195 | 0.012 | 1.388 | |
| locate_images | 0 | 0 | 0 | |
| read10xVisiumAnalysis | 0.000 | 0.000 | 0.001 | |
| read10xVisiumWrapper | 0 | 0 | 0 | |
| registration_block_cor | 4.088 | 0.264 | 4.353 | |
| registration_model | 0.928 | 0.016 | 0.944 | |
| registration_pseudobulk | 0.868 | 0.000 | 0.869 | |
| registration_stats_anova | 3.175 | 0.028 | 3.203 | |
| registration_stats_enrichment | 3.366 | 0.064 | 3.430 | |
| registration_stats_pairwise | 3.182 | 0.020 | 3.202 | |
| registration_wrapper | 4.715 | 0.004 | 4.719 | |
| run_app | 0.001 | 0.000 | 0.001 | |
| sce_to_spe | 22.531 | 2.043 | 25.250 | |
| sig_genes_extract | 2.749 | 0.372 | 3.522 | |
| sig_genes_extract_all | 3.292 | 0.203 | 3.858 | |
| sort_clusters | 0.003 | 0.000 | 0.003 | |
| vis_clus | 31.831 | 3.073 | 35.748 | |
| vis_clus_p | 25.057 | 2.021 | 28.380 | |
| vis_gene | 35.402 | 2.814 | 38.843 | |
| vis_gene_p | 24.956 | 1.807 | 27.393 | |
| vis_grid_clus | 25.153 | 2.168 | 27.888 | |
| vis_grid_gene | 25.656 | 2.437 | 28.697 | |