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This page was generated on 2025-12-04 12:02 -0500 (Thu, 04 Dec 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 4878
merida1macOS 12.7.6 Montereyx86_644.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 4624
taishanLinux (openEuler 24.03 LTS)aarch644.5.0 (2025-04-11) -- "How About a Twenty-Six" 4669
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 165/2361HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
benchdamic 1.16.0  (landing page)
Matteo Calgaro
Snapshot Date: 2025-12-01 13:45 -0500 (Mon, 01 Dec 2025)
git_url: https://git.bioconductor.org/packages/benchdamic
git_branch: RELEASE_3_22
git_last_commit: fcdab2a
git_last_commit_date: 2025-10-29 11:13:16 -0500 (Wed, 29 Oct 2025)
nebbiolo2Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  NO, package depends on 'Maaslin2' which is not available
merida1macOS 12.7.6 Monterey / x86_64  OK    TIMEOUT  skippedskipped
taishanLinux (openEuler 24.03 LTS) / aarch64  OK    OK    ERROR  


CHECK results for benchdamic on taishan

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.

raw results


Summary

Package: benchdamic
Version: 1.16.0
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_1.16.0.tar.gz
StartedAt: 2025-12-02 06:56:16 -0000 (Tue, 02 Dec 2025)
EndedAt: 2025-12-02 07:15:20 -0000 (Tue, 02 Dec 2025)
EllapsedTime: 1144.2 seconds
RetCode: 1
Status:   ERROR  
CheckDir: benchdamic.Rcheck
Warnings: NA

Command output

##############################################################################
##############################################################################
###
### 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_1.16.0.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 ‘1.16.0’
* 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
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
> 
> # Concordance for p-values
> concordance_pvalues <- createConcordance(
+     object = results, slot = "pValMat", colName = "rawP", type = "pvalue"
+ )
> 
> # plot concordances from rank 1 to 50.
> plotConcordance(
+     concordance = concordance_pvalues,
+     threshold = 50
+ )
Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.
ℹ The deprecated feature was likely used in the benchdamic package.
  Please report the issue at <https://github.com/mcalgaro93/benchdamic/issues>.
$concordanceDendrogram

$concordanceHeatmap
Examples with CPU (user + system) or elapsed time > 5s
                   user system elapsed
createConcordance 7.538  0.095  14.076
areaCAT           7.051  0.155   8.436
DA_ALDEx2         5.907  0.196   6.117
fitModels         3.631  0.033   7.457
norm_DESeq2       0.676  1.762   6.775
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’/home/biocbuild/R/R-4.5.0/bin/BATCH: line 60: 1243876 Killed                  ${R_HOME}/bin/R -f ${in} ${opts} ${R_BATCH_OPTIONS} > ${out} 2>&1

 ERROR
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(benchdamic)
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 ERRORs, 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.22-bioc/meat/benchdamic.Rcheck/00check.log’
for details.


Installation output

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 ‘1.16.0’
** 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)

Tests output

benchdamic.Rcheck/tests/testthat.Rout.fail


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)

Example timings

benchdamic.Rcheck/benchdamic-Ex.timings

nameusersystemelapsed
CAT0.0050.0000.004
DA_ALDEx25.9070.1966.117
DA_ANCOM1.0980.0831.184
DA_DESeq23.7090.0273.745
DA_MAST1.7530.0361.794
DA_Maaslin20.2710.0370.328
DA_NOISeq1.3610.0601.425
DA_Seurat2.0210.0122.036
DA_ZicoSeq0.9780.0160.996
DA_basic0.0420.0000.042
DA_corncob0.8730.0160.944
DA_dearseq0.0730.0000.074
DA_edgeR0.2320.0000.233
DA_limma0.0950.0000.095
DA_linda0.0640.0000.065
DA_maaslin30.7410.0040.751
DA_metagenomeSeq0.3170.0040.327
DA_mixMC0.8670.0000.869
RMSE0.0010.0000.000
addKnowledge0.2750.0280.304
areaCAT7.0510.1558.436
checkNormalization0.0000.0000.001
createColors0.0050.0000.005
createConcordance 7.538 0.09514.076
createEnrichment0.3810.0000.767
createMocks0.0030.0000.008
createPositives1.4690.0082.043
createSplits0.0500.0000.079
createTIEC4.3450.0244.380
enrichmentTest0.1690.0000.170
extractDA0.2700.0000.271
extractStatistics0.2650.0000.266
fitDM0.0400.0040.044
fitHURDLE1.0010.0041.411
fitModels3.6310.0337.457
fitNB0.0720.0040.154
fitZIG0.0880.0040.288
fitZINB0.7320.0051.772
getDA0.1200.0040.214
getPositives0.1590.0160.519
getStatistics0.1080.0000.212
get_counts_metadata0.1760.0040.383
iterative_ordering0.0130.0010.034
meanDifferences0.0030.0000.003
norm_CSS0.1000.0000.133
norm_DESeq20.6761.7626.775
norm_TSS0.0450.0220.207
norm_edgeR0.0580.0110.070