##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:tidyexposomics.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings tidyexposomics_0.99.12.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/tidyexposomics.Rcheck’
* using R Under development (unstable) (2026-01-15 r89304)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘tidyexposomics/DESCRIPTION’ ... OK
* this is package ‘tidyexposomics’ version ‘0.99.12’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 30 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 ‘tidyexposomics’ 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 whether startup messages can be suppressed ... 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 data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: OK

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL tidyexposomics
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’
* installing *source* package ‘tidyexposomics’ ...
** this is package ‘tidyexposomics’ version ‘0.99.12’
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** 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 (tidyexposomics)

R Under development (unstable) (2026-01-15 r89304) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
> 
> library(testthat)
> library(tidyexposomics)
Loading required package: MultiAssayExperiment
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
Loading required package: generics

Attaching package: 'generics'

The following objects are masked from 'package:base':

    as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
    setequal, union


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, is.unsorted, lapply,
    mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
    rank, rbind, rownames, sapply, saveRDS, table, tapply, 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: Seqinfo
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("tidyexposomics")
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Log2-Transforming each assay in MultiAssayExperiment.
Log2-Transforming each assay in MultiAssayExperiment.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Log2-Transforming each assay in MultiAssayExperiment.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Scaling each assay in MultiAssayExperiment.
Running multi-omics integration using DIABLO...
Applying DIABLO supervised integration.
Design matrix has changed to include Y; each block will be
            linked to Y.
Extracting top contributing features for specified factors.
Using DIABLO loadings.
Applying percentile-based filtering (>90%).
Selected 39 features contributing to specified factors.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Scaling each assay in MultiAssayExperiment.
Running multi-omics integration using RGCCA...
Applying RGCCA integration.
Extracting top contributing features for specified factors.
Using RGCCA loadings.
Applying percentile-based filtering (>90%).
Selected 39 features contributing to specified factors.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Missing Data Filter threshold: 20%
Filtered metadata variables: age
Filtered rows with high missingness in mRNA: 2
Filtered rows with high missingness in proteomics: 4
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Checking Normality Using Shapiro-Wilk Test
1 Exposure Variables are Normally Distributed
3 Exposure Variables are NOT Normally Distributed
Applying the boxcox_best transformation.
Filtering out 3 non-normal exposure variables.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Identifying common samples.
Subsetting exposure data.
Subsetting omics data.
Performing PCA on Feature Space.
Performing PCA on Sample Space.
Outliers detected: S1
Removing outliers: S1
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Running GLMs.
Skipping alcohol - term not found in model (possibly dropped)
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Running GLMs.
Skipping alcohol - term not found in model (possibly dropped)
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Starting clustering analysis...
Optimal number of clusters for samples: 12
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Log2-Transforming each assay in MultiAssayExperiment.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Log2-Transforming each assay in MultiAssayExperiment.
Creating network from correlation results.
Network added to metadata as: network_omics_feature_cor
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Log2-Transforming each assay in MultiAssayExperiment.
Creating network from correlation results.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Running differential abundance testing.
Processing assay: mRNA
=====================================
tidybulk says: All testing methods use raw counts, irrespective of if scale_abundance
or adjust_abundance have been calculated. Therefore, it is essential to add covariates
such as batch effects (if applicable) in the formula.
=====================================
This message is displayed once per session.
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Processing assay: proteomics
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Differential abundance testing completed.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Running differential abundance testing.
Processing assay: mRNA
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Processing assay: proteomics
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Differential abundance testing completed.
Cannot access http://current.geneontology.org/annotations/goa_human.gaf.gz/goa_human.gaf.gz. 403: Forbidden.
Cannot access http://current.geneontology.org/annotations/goa_human.gaf.gz/goa_human.gaf.gz. 403: Forbidden.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Extracting exposure data...
Calculating mean exposure scores...
Extracting exposure data...
Calculating sum exposure scores...
Extracting exposure data...
Calculating median exposure scores...
Extracting exposure data...
Calculating PCA exposure scores...
Extracting exposure data...
Calculating quantile exposure scores...
Extracting exposure data...
Calculating variance exposure scores...
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Extracting exposure data...
Calculating sum exposure scores...
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Extracting exposure data...
Calculating IRT exposure scores...

Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Extracting exposure data...
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Running differential abundance testing.
Processing assay: mRNA
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Processing assay: proteomics
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Differential abundance testing completed.
Creating network from correlation results.
Network added to metadata as: network_degs
Creating network from correlation results.
Network added to metadata as: network_degs_feature_cor
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Running differential abundance testing.
Processing assay: mRNA
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Processing assay: proteomics
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Differential abundance testing completed.
Scaling each assay in MultiAssayExperiment.
Running multi-omics integration using DIABLO...
Applying DIABLO supervised integration.
Design matrix has changed to include Y; each block will be
            linked to Y.
Extracting top contributing features for specified factors.
Using DIABLO loadings.
Applying percentile-based filtering (>50%).
Selected 0 features contributing to specified factors.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Imputing exposure data using method: median
Imputing omics dataset: mRNA using method: knn
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Scaling each assay in MultiAssayExperiment.
Running multi-omics integration using RGCCA...
Applying RGCCA integration.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Scaling each assay in MultiAssayExperiment.
Running multi-omics integration using DIABLO...
Applying DIABLO supervised integration.
Design matrix has changed to include Y; each block will be
            linked to Y.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Checking Normality Using Shapiro-Wilk Test
4 Exposure Variables are Normally Distributed
0 Exposure Variables are NOT Normally Distributed
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Identifying common samples.
Subsetting exposure data.
Subsetting omics data.
Performing PCA on Feature Space.
Performing PCA on Sample Space.
No outliers detected.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Running differential abundance testing.
Processing assay: mRNA
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Processing assay: proteomics
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Differential abundance testing completed.
Running bootstrap iteration 1 of 3
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Running bootstrap iteration 2 of 3
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Running bootstrap iteration 3 of 3
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
tidybulk says: The design column names are "(Intercept), smokeryes, sexM"
tidybulk says: to access the DE object do `metadata(.)$tidybulk$limma_voom_object`
tidybulk says: to access the raw results (fitted GLM) do `metadata(.)$tidybulk$limma_voom_fit`
Computing feature stability across sensitivity conditions.
Feature stability analysis completed.
Number Of Features Above Threshold Of 0.52:
----------------------------------------
mRNA: 2/128
proteomics: 1/80
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Applying the boxcox_best transformation.
Ensuring all omics datasets are matrices with column names.
Creating SummarizedExperiment objects.
Creating MultiAssayExperiment object.
MultiAssayExperiment created successfully.
Applying the log2 transformation.
[ FAIL 0 | WARN 33 | SKIP 4 | PASS 189 ]

══ Skipped tests (4) ═══════════════════════════════════════════════════════════
• On Bioconductor (4): 'test-extract_top_factor_features.R:4:5',
  'test-extract_top_factor_features.R:48:5',
  'test-run_multiomics_integration.R:3:5',
  'test-run_multiomics_integration.R:59:5'

[ FAIL 0 | WARN 33 | SKIP 4 | PASS 189 ]
> 
> proc.time()
   user  system elapsed 
 42.649   1.507  44.524