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Author: Matthew Hung

Last Updated: 2025/05/30

Source: vignettes/deseq2pip.Rmd
deseq2pip.Rmd
## Warning: replacing previous import 'S4Arrays::makeNindexFromArrayViewport' by
## 'DelayedArray::makeNindexFromArrayViewport' when loading 'SummarizedExperiment'

Run deseq2pip on RNA-seq data 

# create a directory for results, currently set to tempdir()
#save_dir <- "/Users/hungm/The Francis Crick Dropbox/CaladoD/Matthew/github-repos/r-pipelines/deseq2pip/tests/rnaseq/pipeline/"
save_dir <- tempdir()
dir.create(save_dir, recursive = TRUE)
## Warning in dir.create(save_dir, recursive = TRUE): '/tmp/RtmpZnQkvP' already
## exists

Load DESeq2 object processed by nf-core/rnaseq 

# load deseq2 object processed by nf-core/rnaseq
rdata <- system.file("data", "GSE189410.dds.RData", package = "deseq2pip")
tx2gene <- gzfile(system.file("data", "GSE189410.tx2gene.tsv.gz", package = "deseq2pip"))
dds <- import_nfcore_rna(rdata = rdata, tx2gene = tx2gene)

Run RNA pipeline 

# run run pipeline
run_rna_pip(
    dds,
    org = "mouse",
    group_by = "Group2",
    remove_xy = TRUE,
    remove_mt = TRUE,
    quantile = 0.05,
    pals = NULL,
    batch = NULL,
    order = "pxfc",
    save_dir = save_dir)
## renv not initialized, initializing renv
## - The project is out-of-sync -- use `renv::status()` for details.
## The following required packages are not installed:
## - rmarkdown
## Packages must first be installed before renv can snapshot them.
## Use `renv::dependencies()` to see where this package is used in your project.
## 
## The following package(s) will be updated in the lockfile:
## 
## # CRAN -----------------------------------------------------------------------
## - renv   [* -> 1.1.4]
## 
## The version of R recorded in the lockfile will be updated:
## - R      [* -> 4.5.0]
## 
## - Lockfile written to "/tmp/RtmpZnQkvP/logs/renv.lock".
## WARNING: '/tmp/RtmpZnQkvP' already exists
## group_by is not a factor, converting to factor
## group_by is not in the design, adding to design
## Running RNA-seq pipeline with DESeq2pip v1.0.2
## Running quality control pipeline...
## Removing 4050 XY genes out of 54513 total genes...
## Removing 37 MT genes out of 50463 total genes...
## Filtering genes with low expressions...

## Saving DESeq2 object & expressions...
## Running distance analysis pipeline...
## Running batch correction...
## Running PCA and distance analysis...
## group_by is not a factor, converting to factor
## using ntop=500 top features by variance

## using ntop=500 top features by variance

## group_by is not a factor, converting to factor
## using ntop=500 top features by variance

## using ntop=500 top features by variance

## Running PAIRWISE differential expression analysis...
## Running PAIRWISE differential expression analysis...
## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 8 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 951 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 952 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 15579 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 33 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 15579 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 37 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 8 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 1545 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 1546 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 16549 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 19 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 16549 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 30 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 8 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 701 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 702 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 14978 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 34 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 14978 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 39 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Running PAIRWISE gene set enrichment pipeline...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 13 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 13 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 14 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 14 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 4 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 4 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There are ties in the preranked stats (0.03% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There are ties in the preranked stats (0.03% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There are ties in the preranked stats (0.03% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There are ties in the preranked stats (0.03% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There are ties in the preranked stats (0.03% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There are ties in the preranked stats (0.03% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 10 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 10 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 4 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 4 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 12 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 12 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 11 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 11 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 6 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 6 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 8 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 8 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Running PAIRWISE enrichment map pipeline...
## Formatting for enrichmentmap...
## Writing class files for PAIRWISE comparisons...
## Running ONE-TO-ALL differential expression analysis...
## Running ONE-TO-ALL differential expression analysis...
## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## -- replacing outliers and refitting for 501 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)
## estimating dispersions
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 8 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 856 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 858 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 16690 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 18 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 16690 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 24 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## -- replacing outliers and refitting for 504 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)
## estimating dispersions
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 8 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 345 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 347 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 16407 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 33 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 16407 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 35 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## -- replacing outliers and refitting for 607 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)
## estimating dispersions
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 8 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 864 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 863 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 18304 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 32 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 18304 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 36 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Running ONE-TO-ALL gene set enrichment pipeline...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 10 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 10 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 6 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 6 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 9 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 9 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 7 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 7 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 4 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 4 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 3 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Running ONE-TO-ALL enrichment map pipeline...
## Formatting for enrichmentmap...
## Writing class files for ONE-TO-ALL comparisons...
## RNAseq pipeline complete; returning DESeq2 object...
## class: DESeqDataSet 
## dim: 50426 11 
## metadata(1): version
## assays(1): counts
## rownames(50426): 0610005C13Rik 0610006L08Rik ... snoZ159 snoZ196
## rowData names(1): gene
## colnames(11): BM_IgA_1 BM_IgA_2 ... BM_IgM_3 BM_IgM_4
## colData names(6): sample Group1 ... sizeFactor condition

Run deseq2pip on ATAC-seq data 

# create a directory for results, currently set to tempdir()
#save_dir <- "/Users/hungm/The Francis Crick Dropbox/CaladoD/Matthew/github-repos/r-pipelines/deseq2pip/tests/atacseq/pipeline/"
save_dir <- tempdir()
dir.create(save_dir, recursive = TRUE)
## Warning in dir.create(save_dir, recursive = TRUE): '/tmp/RtmpZnQkvP' already
## exists

Load DESeq2 object processed by nf-core/atacseq 

# load deseq2 object processed by nf-core/atacseq
rdata <- system.file("data", "GSE224512.dds.RData", package = "deseq2pip")
annotatePeaks <- gzfile(system.file("data", "GSE224512.annotatePeaks.txt.gz", package = "deseq2pip"))
dds <- import_nfcore_atac(rdata = rdata, annotatePeaks = annotatePeaks)

# subset groups for brevity
dds <- dds[, dds$Group1 %in% c("WT", 'BC', 'BCK')]

Run ATAC pipeline 

# run atac pipeline
run_atac_pip(
    dds,
    org = "mouse",
    group_by = "Group1",
    remove_xy = TRUE,
    remove_mt = TRUE,
    quantile = 0.05,
    pals = NULL,
    batch = NULL,
    order = "pxfc",
    TSS = TRUE,
    save_dir = save_dir)
## renv already initialized, restoring renv
## - The library is already synchronized with the lockfile.
## WARNING: '/tmp/RtmpZnQkvP' already exists
## group_by is not a factor, converting to factor
## group_by is not in the design, adding to design
## Running ATAC-seq pipeline with DESeq2pip v1.0.2
## Running quality control pipeline...
## Removing 3331 XY genes out of 74851 total genes...
## Removing 2 MT genes out of 71520 total genes...
## Filtering genes with low expressions...

## Saving DESeq2 object & expressions...
## Running distance analysis pipeline...
## Running batch correction...
## Running PCA and distance analysis...
## using ntop=500 top features by variance

## group_by is not a factor, converting to factor
## using ntop=500 top features by variance

## using ntop=500 top features by variance

## Running PAIRWISE differential expression analysis for ALL PEAKS...
## Running PAIRWISE differential expression analysis...
## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 9 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 1373 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 1373 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 59953 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 28 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 59953 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 34 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 9 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 157 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 158 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 58465 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 22 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 58465 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 23 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 9 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 180 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 180 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 46352 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 17 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 46352 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 33 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Generating PAIRWISE peak annotation plots...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Filtering differentially expressed peaks...
## Processing peak annotations...
## Plotting pie charts...
## Creating pie charts for 1391 peaks in All DE Peaks...
## Creating pie charts for 623 peaks in Upregulated DE Peaks...
## Creating pie charts for 768 peaks in Downregulated DE Peaks...
## Saving pie charts to PDF...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Filtering differentially expressed peaks...
## Processing peak annotations...
## Plotting pie charts...
## Creating pie charts for 187 peaks in All DE Peaks...
## Creating pie charts for 124 peaks in Upregulated DE Peaks...
## Creating pie charts for 63 peaks in Downregulated DE Peaks...
## Saving pie charts to PDF...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Filtering differentially expressed peaks...
## Processing peak annotations...
## Plotting pie charts...
## Creating pie charts for 190 peaks in All DE Peaks...
## Creating pie charts for 93 peaks in Upregulated DE Peaks...
## Creating pie charts for 97 peaks in Downregulated DE Peaks...
## Saving pie charts to PDF...
## Running ONE-TO-ALL differential expression analysis for ALL PEAKS...
## Running ONE-TO-ALL differential expression analysis...
## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## -- replacing outliers and refitting for 2 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)
## estimating dispersions
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 9 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 210 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 212 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 54377 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 29 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 54377 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 33 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## -- replacing outliers and refitting for 6 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)
## estimating dispersions
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 9 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 768 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 768 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 59222 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 16 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 59222 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 22 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## -- replacing outliers and refitting for 6 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)
## estimating dispersions
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 9 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 61343 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 61343 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Generating ONE-TO-ALL peak annotation plots for ALL PEAKS...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Filtering differentially expressed peaks...
## Processing peak annotations...
## Plotting pie charts...
## Creating pie charts for 241 peaks in All DE Peaks...
## Creating pie charts for 122 peaks in Upregulated DE Peaks...
## Creating pie charts for 119 peaks in Downregulated DE Peaks...
## Saving pie charts to PDF...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Filtering differentially expressed peaks...
## Processing peak annotations...
## Plotting pie charts...
## Creating pie charts for 778 peaks in All DE Peaks...
## Creating pie charts for 395 peaks in Upregulated DE Peaks...
## Creating pie charts for 383 peaks in Downregulated DE Peaks...
## Saving pie charts to PDF...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Filtering differentially expressed peaks...
## Processing peak annotations...
## Plotting pie charts...
## Creating pie charts for 1 peaks in All DE Peaks...
## Creating pie charts for 1 peaks in Upregulated DE Peaks...
## Saving pie charts to PDF...
## NULL
## Running PAIRWISE differential expression analysis for TSS PEAKS...
## Running PAIRWISE differential expression analysis...
## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 1 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 357 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 357 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 11770 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 30 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 11770 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 34 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 1 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 12360 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 12360 rows containing missing values or values outside the scale range
## (`geom_text()`).

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 1 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 24 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 24 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 11129 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 3 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 11129 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 7 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Running PAIRWISE gene set enrichment pipeline for TSS PEAKS...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 8 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 8 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 11 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 11 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 12 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 12 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 10 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 10 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 7 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 7 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 10 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 10 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There were 1 pathways for which P-values were not calculated properly due to unbalanced (positive and negative) gene-level statistic values. For such pathways pval, padj, NES, log2err are set to NA. You can try to increase the value of the argument nPermSimple (for example set it nPermSimple = 10000)
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 7 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 7 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Running PAIRWISE enrichment map pipeline for TSS PEAKS...
## Formatting for enrichmentmap...
## Writing class files for PAIRWISE comparisons...
## Running ONE-TO-ALL differential expression analysis for TSS PEAKS...
## Running ONE-TO-ALL differential expression analysis...
## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 1 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 13 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 13 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 12333 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 30 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 12333 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 33 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 1 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: ggrepel: 169 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: ggrepel: 171 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: Removed 11693 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 22 unlabeled data points (too many overlaps). Consider increasing max.overlaps
## WARNING: Removed 11693 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: ggrepel: 26 unlabeled data points (too many overlaps). Consider increasing max.overlaps

## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## using 'ashr' for LFC shrinkage. If used in published research, please cite:
##     Stephens, M. (2016) False discovery rates: a new deal. Biostatistics, 18:2.
##     https://doi.org/10.1093/biostatistics/kxw041
## Combining row metadata to results...
## Removed 1 rows with NA values or invalid gene symbols
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: No shared levels found between `names(values)` of the manual scale and the
## data's colour values.
## WARNING: No shared levels found between `names(values)` of the manual scale and the
## data's colour values.

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## WARNING: no non-missing arguments to max; returning -Inf
## WARNING: NaNs produced
## WARNING: Removed 12381 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 12381 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Running ONE-TO-ALL gene set enrichment pipeline for TSS PEAKS...
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 9 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 9 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 5 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 6 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 6 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## Converting baseMean to numeric
## Converting log2FoldChange to numeric
## Converting padj to numeric
## Converting rank to numeric
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There were 7 pathways for which P-values were not calculated properly due to unbalanced (positive and negative) gene-level statistic values. For such pathways pval, padj, NES, log2err are set to NA. You can try to increase the value of the argument nPermSimple (for example set it nPermSimple = 10000)
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: There were 2 pathways for which P-values were not calculated properly due to unbalanced (positive and negative) gene-level statistic values. For such pathways pval, padj, NES, log2err are set to NA. You can try to increase the value of the argument nPermSimple (for example set it nPermSimple = 10000)
## leading edge analysis...
## done...
## using 'fgsea' for GSEA analysis, please cite Korotkevich et al (2019).
## preparing geneSet collections...
## GSEA analysis...
## WARNING: For some of the pathways the P-values were likely overestimated. For such pathways log2err is set to NA.
## WARNING: For some pathways, in reality P-values are less than 1e-10. You can set the `eps` argument to zero for better estimation.
## leading edge analysis...
## done...
## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 6 rows containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 6 rows containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Converting NES to numeric
## Converting pvalue to numeric
## Converting qvalue to numeric
## WARNING: Ignoring unknown aesthetics: stroke
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).
## WARNING: Removed 1 row containing missing values or values outside the scale range
## (`geom_text()`).

## Running ONE-TO-ALL enrichment map pipeline for TSS PEAKS...
## Formatting for enrichmentmap...
## Writing class files for ONE-TO-ALL comparisons...
## ATACseq pipeline complete; returning DESeq2 object...
## class: DESeqDataSet 
## dim: 69431 13 
## metadata(1): version
## assays(2): counts vst
## rownames(69431): Interval_1 Interval_2 ... Interval_74799
##   Interval_74821
## rowData names(20): peaks Chr ... gene TSS
## colnames(13): WT_REP4 BCK_REP5 ... BC_REP2 BC_REP1
## colData names(4): sample Group1 Group2 sizeFactor