The following invocations of OpenMS/pyprophet/tric are included in:
This script includes the process for generating a local, comet-based transition library from DDA samples generated locally as well as the steps used when processing the downloaded transition libraries.
In this first block, I will set a couple of variables and source a file containing the parameters for the rest of the script.
The raw data files provide opportunities to make sure that the later invocations of openMS/etc will actually work; for example, if there are too few transitions observed here, one should not be surprised if pyprophet and tric fail later.
sample_sheet <- glue::glue("sample_sheets/Mtb_dia_samples_{ver}.xlsx")
savefile <- "mzxml_dia_data_20180913.rda"
metadata <- openxlsx::read.xlsx(sample_sheet)
keeper_idx <- !grepl(pattern="^#", x=metadata[["sampleid"]])
metadata <- metadata[keeper_idx, ]
knitr::kable(metadata)
sampleid | TubeID | tubelabel | FigureReplicate | Figure.Name | Sample.Description | Bio.Replicate | LC.Run | MS.Run | Technical.Replicate | Replicate.State | rep | run | expt_id | Genotype | Collection.Type | Condition | batch | windowsize | enzyme | harvestdate | prepdate | rundate | runinfo | rawfile | Filename | mzmlfile | dia_scored | tuberculist_scored | include_exclude | Run_note |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2019_0709Briken01 | 6.24.19–4 | WT H37Rv Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken01 | NA | NA | NA | wt_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken01.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken01.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken01.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken01_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken02 | 6.24.19–5 | H37Rv ΔEsx-5A; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken02 | NA | NA | NA | dt_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken02.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken02.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken02.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken02_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken03 | 6.24.19–6 | H37Rv ΔEsx-5A Complement; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken03 | NA | NA | NA | cp_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken03.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken03.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken03.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken03_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken04 | 6.24.19–10 | WT H37Rv Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken04 | NA | NA | NA | wt_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken04.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken04.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken04.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken04_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken05 | 6.24.19–11 | H37Rv ΔEsx-5A; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken05 | NA | NA | NA | dt_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken05.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken05.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken05.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken05_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken06 | 6.24.19–12 | H37Rv ΔEsx-5A Complement; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken06 | NA | NA | NA | cp_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken06.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken06.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken06.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken06_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken07 | 6.24.19–16 | WT H37Rv Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken07 | NA | NA | NA | wt_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken07.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken07.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken07.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken07_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken08 | 6.24.19–17 | H37Rv ΔEsx-5A; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken08 | NA | NA | NA | dt_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken08.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken08.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken08.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken08_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken09 | 6.24.19–18 | H37Rv ΔEsx-5A Complement; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken09 | NA | NA | NA | cp_cf | early | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken09.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken09.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken09.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken09_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken10 | 6.24.19–22 | WT H37Rv Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken10 | NA | NA | NA | wt_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken10.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken10.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken10.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken10_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken11 | 6.24.19–23 | H37Rv ΔEsx-5A; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken11 | NA | NA | NA | dt_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken11.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken11.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken11.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken11_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken12 | 6.24.19–24 | H37Rv ΔEsx-5A Complement; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken12 | NA | NA | NA | cp_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken12.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken12.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken12.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken12_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken13 | 6.24.19–28 | WT H37Rv Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken13 | NA | NA | NA | wt_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken13.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken13.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken13.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken13_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken14 | 6.24.19–29 | H37Rv ΔEsx-5A; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken14 | NA | NA | NA | dt_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken14.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken14.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken14.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken14_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken15 | 6.24.19–30 | H37Rv ΔEsx-5A Complement; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken15 | NA | NA | NA | cp_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken15.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken15.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken15.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken15_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken16 | 6.24.19–34 | WT H37Rv Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken16 | NA | NA | NA | wt_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken16.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken16.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken16.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken16_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken17 | 6.24.19–35 | H37Rv ΔEsx-5A; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken17 | NA | NA | NA | dt_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken17.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken17.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken17.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken17_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
2019_0709Briken18 | 6.24.19–36 | H37Rv ΔEsx-5A Complement; Culture Filtrate | NA | NA | NA | b20190610 | l20190709 | m20190709 | t20190709 | NA | a | 2019_0709Briken18 | NA | NA | NA | cp_cf | late | 8mz | NA | NA | NA | NA | NA | preprocessing/00_raw/2019_0709Briken18.raw | preprocessing/01mzXML/dia/20190718/2019_0709Briken18.mzXML | preprocessing/01mzML/dia/20190718/2019_0709Briken18.mzML | preprocessing/08pyprophet/20190718/whole_8mz_tuberculist/2019_0709Briken18_vs_20190718_whole_HCD_dia_scored.tsv | NA | NA | NA |
if (file.exists(savefile)) {
load(savefile)
} else {
mzxml_data <- extract_msraw_data(metadata, parallel=FALSE,
allow_window_overlap=FALSE,
file_column="Filename",
savefile=savefile)
mzml_data <- extract_msraw_data(metadata, parallel=FALSE,
format="mzML",
allow_window_overlap=FALSE,
file_column="mzmlfile",
savefile="testing.rda")
}
intensity_boxplot <- plot_mzxml_boxplot(mzxml_data)
## Adding 2019_0709Briken01
## Adding 2019_0709Briken02
## Adding 2019_0709Briken03
## Adding 2019_0709Briken04
## Adding 2019_0709Briken05
## Adding 2019_0709Briken06
## Adding 2019_0709Briken07
## Adding 2019_0709Briken08
## Adding 2019_0709Briken09
## Adding 2019_0709Briken10
## Adding 2019_0709Briken11
## Adding 2019_0709Briken12
## Adding 2019_0709Briken13
## Adding 2019_0709Briken14
## Adding 2019_0709Briken15
## Adding 2019_0709Briken16
## Adding 2019_0709Briken17
## Adding 2019_0709Briken18
## This data will benefit from being displayed on the log scale.
## If this is not desired, set scale='raw'
## Some entries are 0. We are on log scale, adding 1 to the data.
## Changed 86349 zero count features.
## Writing the image to: images/20180913_dia_mzxml_intensities-v20190718.png and calling dev.off().
## Adding 2019_0709Briken01
## Adding 2019_0709Briken02
## Adding 2019_0709Briken03
## Adding 2019_0709Briken04
## Adding 2019_0709Briken05
## Adding 2019_0709Briken06
## Adding 2019_0709Briken07
## Adding 2019_0709Briken08
## Adding 2019_0709Briken09
## Adding 2019_0709Briken10
## Adding 2019_0709Briken11
## Adding 2019_0709Briken12
## Adding 2019_0709Briken13
## Adding 2019_0709Briken14
## Adding 2019_0709Briken15
## Adding 2019_0709Briken16
## Adding 2019_0709Briken17
## Adding 2019_0709Briken18
## Writing the image to: images/20180913_dia_mzxml_retention-v20190718.png and calling dev.off().
## Adding 2019_0709Briken01
## Adding 2019_0709Briken02
## Adding 2019_0709Briken03
## Adding 2019_0709Briken04
## Adding 2019_0709Briken05
## Adding 2019_0709Briken06
## Adding 2019_0709Briken07
## Adding 2019_0709Briken08
## Adding 2019_0709Briken09
## Adding 2019_0709Briken10
## Adding 2019_0709Briken11
## Adding 2019_0709Briken12
## Adding 2019_0709Briken13
## Adding 2019_0709Briken14
## Adding 2019_0709Briken15
## Adding 2019_0709Briken16
## Adding 2019_0709Briken17
## Adding 2019_0709Briken18
## Writing the image to: images/20180913_dia_mzxml_mzbase-v20190718.png and calling dev.off().
## Adding 2019_0709Briken01
## Adding 2019_0709Briken02
## Adding 2019_0709Briken03
## Adding 2019_0709Briken04
## Adding 2019_0709Briken05
## Adding 2019_0709Briken06
## Adding 2019_0709Briken07
## Adding 2019_0709Briken08
## Adding 2019_0709Briken09
## Adding 2019_0709Briken10
## Adding 2019_0709Briken11
## Adding 2019_0709Briken12
## Adding 2019_0709Briken13
## Adding 2019_0709Briken14
## Adding 2019_0709Briken15
## Adding 2019_0709Briken16
## Adding 2019_0709Briken17
## Adding 2019_0709Briken18
## Writing the image to: images/20180913_dia_mzxml_scanintensity-v20190718.png and calling dev.off().
In block 15 of dia_invocation_20180913.sh the command used is prested and copied here for interactive running.
echo "Converting the Tuberculist libraries to pqp."
TUBERCULIST_TRAML="preprocessing/05spectral_libraries/Mtb_TubercuList-R27_iRT_UPS_noMox_noMC_sall_osw_decoy.TraML"
echo "The input is: ${TUBERCULIST_TRAML}"
echo "The output is: ${TUBERCULIST_PQP}"
mkdir -p $(dirname ${TUBERCULIST_PQP})
TargetedFileConverter \
-in "${TUBERCULIST_TRAML}" \
-in_type TraML \
-out "${TUBERCULIST_PQP}" \
-out_type pqp \
2>"${TUBERCULIST_PQP}_convert.log" 1>&2
block 16 contains the commands used to run openswathworkflow and pyprophet. Those are repeated here in order to test them interactively when needed.
echo "Invoking the OpenSwathWorkflow using the tuberculist transitions."
base_mzxmldir="preprocessing/01mzXML/dia/${VERSION}"
swath_inputs=$(/bin/ls "${base_mzxmldir}")
echo "Checking in, the inputs are: ${swath_inputs}"
mkdir -p "${TUBERCULIST_OUTDIR}"
pypdir="${PYPROPHET_OUTDIR}_tuberculist"
echo "Creating pyprophet output directory: ${pypdir}."
mkdir -p "${pypdir}"
for input in ${swath_inputs}
do
in_mzxml="${base_mzxmldir}/${input}"
name=$(basename "${input}" .mzXML)
echo "Starting openswath run of ${name} using ${MZ_WINDOWS} windows at $(date)."
tb_output_prefix="${TUBERCULIST_OUTDIR}/${name}_vs_${VERSION}_${TYPE}_${DDA_METHOD}_dia"
pyprophet_output_prefix="${pypdir}/${name}_vs_${VERSION}_${TYPE}_${DDA_METHOD}_dia"
echo "Deleting previous swath output file: ${tb_output_prefix}.osw"
rm -f "${tb_output_prefix}.osw"
OpenSwathWorkflow \
-force \
-ini "parameters/openms_${VERSION}.ini" \
-in "${in_mzxml}" \
-swath_windows_file "windows/openswath_${name}.txt" \
-tr "${TUBERCULIST_PQP}" \
-out_osw "${tb_output_prefix}.osw" \
2>"${tb_output_prefix}_osw.log" 1>&2
if [[ "$?" -ne "0" ]]; then
echo "OpenSwathWorkflow for ${name} failed."
fi
rm -f "${tb_output_prefix}_scored.osw"
echo "Scoring individual swath run: ${tb_output_prefix}"
pyprophet \
score \
--in "${tb_output_prefix}.osw" \
--out "${pyprophet_output_prefix}_scored.osw" \
2>>"${pyprophet_output_prefix}_pyprophet_all.log" 1>&2
rm -f "${pyprophet_output_prefix}_scored.tsv"
echo "Exporting individual swath run: to ${pyprophet_output_prefix}_scored.tsv"
pyprophet \
export \
--in "${pyprophet_output_prefix}_scored.osw" \
--out "${pyprophet_output_prefix}_scored.tsv" \
2>>"${pyprophet_output_prefix}_pyprophet_export.log" 1>&2
## ok something is fubar, the stupid tsv files are being written in the cwd as run_filename.tsv
## No matter what I do!
mv "${input}.tsv" "${pyprophet_output_prefix}_scored.tsv"
if [[ "$?" -ne "0" ]]; then
echo "Exporting ${pyprophet_output_prefix}_scored.tsv failed."
fi
done
Finally, block 17 of the invocation script provides the command used to make the final, feature-aligned data which is used by SWATH2stats and friends. In addition, it generates a matrix of intensities by sample and some metadata. Once again, it is copy/pasted here to allow interactive testing.
tric_tb="${TRIC_OUTDIR}_tuberculist"
mkdir -p "${tric_tb}"
feature_alignment.py \
--force \
--in "./${pypdir}/"*.tsv \
--out "${tric_tb}/${SEARCH_METHOD}_${DDA_METHOD}.tsv" \
--out_matrix "${tric_tb}/${DDA_METHOD}_outmatrix.tsv" \
--out_meta "${tric_tb}/${DDA_METHOD}_meta.tsv" \
2>"${tric_tb}/feature_alignment.err" \
1>"${tric_tb}/feature_alignment.out"
echo "Wrote final output to ${tric_tb}/${SEARCH_METHOD}_${DDA_METHOD}.tsv"
if (!isTRUE(get0("skip_load"))) {
message(paste0("This is hpgltools commit: ", get_git_commit()))
this_save <- paste0(gsub(pattern="\\.Rmd", replace="", x=rmd_file), "-v", ver, ".rda.xz")
message(paste0("Saving to ", this_save))
tmp <- sm(saveme(filename=this_save))
pander::pander(sessionInfo())
}
## If you wish to reproduce this exact build of hpgltools, invoke the following:
## > git clone http://github.com/abelew/hpgltools.git
## > git reset 083922869a37724ece10beed7b0bb758a179fdfb
## This is hpgltools commit: Thu Oct 17 11:43:00 2019 -0400: 083922869a37724ece10beed7b0bb758a179fdfb
## Saving to 02_preprocessing-v20190718-v20190718.rda.xz
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
locale: LC_CTYPE=en_US.UTF-8, LC_NUMERIC=C, LC_TIME=en_US.UTF-8, LC_COLLATE=en_US.UTF-8, LC_MONETARY=en_US.UTF-8, LC_MESSAGES=en_US.UTF-8, LC_PAPER=en_US.UTF-8, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.UTF-8 and LC_IDENTIFICATION=C
attached base packages: parallel, stats, graphics, grDevices, utils, datasets, methods and base
other attached packages: hpgltools(v.1.0), Biobase(v.2.45.1) and BiocGenerics(v.0.31.6)
loaded via a namespace (and not attached): backports(v.1.1.5), fastmatch(v.1.1-0), BiocFileCache(v.1.9.1), plyr(v.1.8.4), igraph(v.1.2.4.1), lazyeval(v.0.2.2), splines(v.3.6.1), BiocParallel(v.1.19.3), usethis(v.1.5.1), GenomeInfoDb(v.1.21.2), ggplot2(v.3.2.1), urltools(v.1.7.3), sva(v.3.33.1), digest(v.0.6.21), foreach(v.1.4.7), htmltools(v.0.4.0), GOSemSim(v.2.11.0), viridis(v.0.5.1), GO.db(v.3.8.2), gdata(v.2.18.0), magrittr(v.1.5), memoise(v.1.1.0), doParallel(v.1.0.15), openxlsx(v.4.1.0.1), limma(v.3.41.18), remotes(v.2.1.0), graphlayouts(v.0.5.0), Biostrings(v.2.53.2), annotate(v.1.63.0), matrixStats(v.0.55.0), askpass(v.1.1), enrichplot(v.1.5.2), prettyunits(v.1.0.2), colorspace(v.1.4-1), blob(v.1.2.0), rappdirs(v.0.3.1), ggrepel(v.0.8.1), xfun(v.0.10), dplyr(v.0.8.3), jsonlite(v.1.6), callr(v.3.3.2), crayon(v.1.3.4), RCurl(v.1.95-4.12), genefilter(v.1.67.1), lme4(v.1.1-21), zeallot(v.0.1.0), survival(v.2.44-1.1), iterators(v.1.0.12), glue(v.1.3.1), polyclip(v.1.10-0), gtable(v.0.3.0), zlibbioc(v.1.31.0), XVector(v.0.25.0), DelayedArray(v.0.11.8), pkgbuild(v.1.0.6), scales(v.1.0.0), DOSE(v.3.11.2), DBI(v.1.0.0), Rcpp(v.1.0.2), viridisLite(v.0.3.0), xtable(v.1.8-4), progress(v.1.2.2), gridGraphics(v.0.4-1), europepmc(v.0.3), bit(v.1.1-14), stats4(v.3.6.1), httr(v.1.4.1), fgsea(v.1.11.1), RColorBrewer(v.1.1-2), gplots(v.3.0.1.1), ellipsis(v.0.3.0), pkgconfig(v.2.0.3), XML(v.3.98-1.20), farver(v.1.1.0), dbplyr(v.1.4.2), ggplotify(v.0.0.4), tidyselect(v.0.2.5), rlang(v.0.4.0), reshape2(v.1.4.3), AnnotationDbi(v.1.47.1), munsell(v.0.5.0), tools(v.3.6.1), cli(v.1.1.0), RSQLite(v.2.1.2), ggridges(v.0.5.1), devtools(v.2.2.1), evaluate(v.0.14), stringr(v.1.4.0), yaml(v.2.2.0), processx(v.3.4.1), knitr(v.1.25), bit64(v.0.9-7), fs(v.1.3.1), tidygraph(v.1.1.2), pander(v.0.6.3), zip(v.2.0.4), caTools(v.1.17.1.2), purrr(v.0.3.2), ggraph(v.2.0.0), nlme(v.3.1-141), xml2(v.1.2.2), DO.db(v.2.9), biomaRt(v.2.41.9), compiler(v.3.6.1), pbkrtest(v.0.4-7), rstudioapi(v.0.10), curl(v.4.2), variancePartition(v.1.15.8), testthat(v.2.2.1), tibble(v.2.1.3), tweenr(v.1.0.1), stringi(v.1.4.3), highr(v.0.8), ps(v.1.3.0), GenomicFeatures(v.1.37.4), desc(v.1.2.0), lattice(v.0.20-38), Matrix(v.1.2-17), nloptr(v.1.2.1), vctrs(v.0.2.0), pillar(v.1.4.2), lifecycle(v.0.1.0), BiocManager(v.1.30.8), triebeard(v.0.3.0), cowplot(v.1.0.0), data.table(v.1.12.4), bitops(v.1.0-6), rtracklayer(v.1.45.6), GenomicRanges(v.1.37.17), qvalue(v.2.17.0), colorRamps(v.2.3), R6(v.2.4.0), KernSmooth(v.2.23-16), gridExtra(v.2.3), IRanges(v.2.19.17), sessioninfo(v.1.1.1), codetools(v.0.2-16), boot(v.1.3-23), MASS(v.7.3-51.4), gtools(v.3.8.1), assertthat(v.0.2.1), pkgload(v.1.0.2), SummarizedExperiment(v.1.15.9), openssl(v.1.4.1), rprojroot(v.1.3-2), withr(v.2.1.2), GenomicAlignments(v.1.21.7), Rsamtools(v.2.1.7), S4Vectors(v.0.23.25), GenomeInfoDbData(v.1.2.1), mgcv(v.1.8-29), hms(v.0.5.1), clusterProfiler(v.3.13.0), grid(v.3.6.1), tidyr(v.1.0.0), minqa(v.1.2.4), rvcheck(v.0.1.5), rmarkdown(v.1.16), ggforce(v.0.3.1) and base64enc(v.0.1-3)