Matteo Calgaro
| Snapshot Date: 2025-10-23 14:17 -0400 (Thu, 23 Oct 2025) |
| git_url: https://git.bioconductor.org/packages/benchdamic |
| git_branch: devel |
| git_last_commit: 7c5727b |
| git_last_commit_date: 2025-10-09 09:40:05 -0400 (Thu, 09 Oct 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-10-24 12:07 -0400 (Fri, 24 Oct 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4898 |
| lconway | macOS 12.7.6 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4688 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4634 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4658 |
| 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 165/2359 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| benchdamic 1.15.4 (landing page) Matteo Calgaro
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.6 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | TIMEOUT | ||||||||||
|
To the developers/maintainers of the benchdamic package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/benchdamic.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: benchdamic |
| Version: 1.15.4 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:benchdamic.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings benchdamic_1.15.4.tar.gz |
| StartedAt: 2025-10-21 04:49:53 -0000 (Tue, 21 Oct 2025) |
| EndedAt: 2025-10-21 05:30:21 -0000 (Tue, 21 Oct 2025) |
| EllapsedTime: 2428.8 seconds |
| RetCode: None |
| Status: TIMEOUT |
| CheckDir: benchdamic.Rcheck |
| Warnings: NA |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:benchdamic.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings benchdamic_1.15.4.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/benchdamic.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘benchdamic/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘benchdamic’ version ‘1.15.4’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 32 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable. Move as many as possible to Suggests and
use conditionally.
* 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 ‘benchdamic’ 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 ... NOTE
Namespace in Imports field not imported from: ‘microbiome’
All declared Imports should be used.
* 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 ... NOTE
Non-topic package-anchored link(s) in Rd file 'norm_DESeq2.Rd':
‘[DESeq2]{estimateSizeFactors}’
See section 'Cross-references' in the 'Writing R Extensions' manual.
* 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 ... ERROR
Running examples in ‘benchdamic-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: plotConcordance
> ### Title: plotConcordance
> ### Aliases: plotConcordance
>
> ### ** Examples
>
> data(ps_plaque_16S)
>
> # Balanced design
> my_splits <- createSplits(
+ object = ps_plaque_16S, varName = "HMP_BODY_SUBSITE", balanced = TRUE,
+ paired = "RSID", N = 10 # N = 100 suggested
+ )
Warning in createSplits(object = ps_plaque_16S, varName = "HMP_BODY_SUBSITE", :
The variable HMP_BODY_SUBSITE is not a factor. Coercing to factor.
Working on 30 paired samples. 2 repeated measures for each RSID ID.
>
> # Make sure the subject ID variable is a factor
> phyloseq::sample_data(ps_plaque_16S)[, "RSID"] <- as.factor(
+ phyloseq::sample_data(ps_plaque_16S)[["RSID"]])
>
> # Initialize some limma based methods
> my_limma <- set_limma(design = ~ RSID + HMP_BODY_SUBSITE,
+ coef = "HMP_BODY_SUBSITESupragingival Plaque",
+ norm = c("TMM", "CSS"))
Warning in set_limma(design = ~RSID + HMP_BODY_SUBSITE, coef = "HMP_BODY_SUBSITESupragingival Plaque", :
DA_limma
One or more elements into 'norm' are not native to edgeR.
>
> # Set the normalization methods according to the DA methods
> my_norm <- setNormalizations(fun = c("norm_edgeR", "norm_CSS"),
+ method = c("TMM", "CSS"))
>
> # Run methods on split datasets
> results <- runSplits(split_list = my_splits, method_list = my_limma,
+ normalization_list = my_norm, object = ps_plaque_16S)
- Subset1
- Comparison1
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison2
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison3
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison4
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison5
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison6
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison7
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison8
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison9
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison10
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Subset2
- Comparison1
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison2
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison3
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison4
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison5
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison6
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=TMM, weights=FALSE
Differential abundance on TMM normalized data
Estimating Differential Abundance without weighting
Extracting results for HMP_BODY_SUBSITESupragingival Plaque coefficient
- Comparison7
Splitting the samples...
Keeping taxa with more than 0 counts in more than 0 samples.
Computing normalizations...
+ Running now:norm_edgeR
Parameters:method=TMM
NF.TMM column has been added.
+ Running now:norm_CSS
Parameters:method=CSS
Default value being used.
NF.CSS column has been added.
Differential abundance:
* Running now:DA_limma
Parameters:assay_name=counts, pseudo_count=FALSE, design=~RSID + HMP_BODY_SUBSITE, coef=HMP_BODY_SUBSITESupragingival Plaque, norm=CSS, weights=FALSE
Warning in DA_limma(object = new("phyloseq", otu_table = new("otu_table", :
DA_limma
CSS normalization is not a native edgeR normalization. Make sure you know what you are doing, otherwise choose between 'TMM', 'TMMwsp', 'RLE', 'upperquartile', 'posupperquartile', or 'none'.
Automatically converting NF.CSS scaling/size factors to normalization factors.
Differential abundance on CSS normalized data
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
createConcordance 8.064 0.083 10.229
areaCAT 6.102 0.067 6.363
DA_ALDEx2 5.235 0.283 5.533
createTIEC 4.823 0.106 6.290
fitModels 4.063 0.377 6.327
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘testthat.R’
benchdamic.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R/bin/R CMD INSTALL benchdamic ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’ * installing *source* package ‘benchdamic’ ... ** this is package ‘benchdamic’ version ‘1.15.4’ ** using staged installation ** R ** data *** moving datasets to lazyload DB ** inst ** byte-compile and prepare package for lazy loading Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics' Also defined by ‘spam’ ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics' Also defined by ‘spam’ ** testing if installed package can be loaded from final location Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics' Also defined by ‘spam’ ** testing if installed package keeps a record of temporary installation path * DONE (benchdamic)
benchdamic.Rcheck/tests/testthat.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: aarch64-unknown-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(benchdamic)
benchdamic.Rcheck/benchdamic-Ex.timings
| name | user | system | elapsed | |
| CAT | 0.004 | 0.000 | 0.005 | |
| DA_ALDEx2 | 5.235 | 0.283 | 5.533 | |
| DA_ANCOM | 1.110 | 0.020 | 1.134 | |
| DA_DESeq2 | 3.882 | 0.104 | 3.997 | |
| DA_MAST | 1.757 | 0.067 | 1.826 | |
| DA_Maaslin2 | 0.374 | 0.009 | 0.392 | |
| DA_NOISeq | 1.279 | 0.055 | 1.341 | |
| DA_Seurat | 2.299 | 0.028 | 2.334 | |
| DA_ZicoSeq | 0.998 | 0.000 | 1.000 | |
| DA_basic | 0.042 | 0.000 | 0.043 | |
| DA_corncob | 0.879 | 0.020 | 0.941 | |
| DA_dearseq | 0.072 | 0.000 | 0.074 | |
| DA_edgeR | 0.236 | 0.000 | 0.237 | |
| DA_limma | 0.095 | 0.000 | 0.096 | |
| DA_linda | 0.065 | 0.000 | 0.066 | |
| DA_maaslin3 | 0.782 | 0.024 | 0.817 | |
| DA_metagenomeSeq | 0.336 | 0.004 | 0.342 | |
| DA_mixMC | 0.981 | 0.023 | 1.012 | |
| RMSE | 0.001 | 0.000 | 0.001 | |
| addKnowledge | 0.213 | 0.001 | 0.215 | |
| areaCAT | 6.102 | 0.067 | 6.363 | |
| checkNormalization | 0.000 | 0.000 | 0.001 | |
| createColors | 0.005 | 0.000 | 0.006 | |
| createConcordance | 8.064 | 0.083 | 10.229 | |
| createEnrichment | 0.377 | 0.000 | 0.381 | |
| createMocks | 0.003 | 0.000 | 0.003 | |
| createPositives | 1.544 | 0.016 | 1.573 | |
| createSplits | 0.044 | 0.004 | 0.048 | |
| createTIEC | 4.823 | 0.106 | 6.290 | |
| enrichmentTest | 0.200 | 0.001 | 0.402 | |
| extractDA | 0.297 | 0.012 | 0.618 | |
| extractStatistics | 0.293 | 0.004 | 0.601 | |
| fitDM | 0.050 | 0.000 | 0.101 | |
| fitHURDLE | 1.100 | 0.036 | 2.576 | |
| fitModels | 4.063 | 0.377 | 6.327 | |
| fitNB | 0.137 | 0.060 | 0.197 | |
| fitZIG | 0.093 | 0.008 | 0.101 | |
| fitZINB | 0.662 | 0.060 | 0.725 | |
| getDA | 0.110 | 0.011 | 0.123 | |
| getPositives | 0.110 | 0.012 | 0.122 | |
| getStatistics | 0.096 | 0.012 | 0.108 | |
| get_counts_metadata | 0.154 | 0.012 | 0.170 | |
| iterative_ordering | 0.009 | 0.004 | 0.013 | |
| meanDifferences | 0.003 | 0.000 | 0.002 | |
| norm_CSS | 0.099 | 0.004 | 0.103 | |
| norm_DESeq2 | 0.698 | 0.016 | 0.749 | |
| norm_TSS | 0.051 | 0.004 | 0.055 | |
| norm_edgeR | 0.054 | 0.008 | 0.063 | |