Package: diffwrap 0.6-3

Vidal Fey

diffwrap: Differential Expression Analysis of RNA-Seq Data

Functions for differential expression analysis of read counts from messenger RNA (mRNA) sequencing (RNA-Seq) data or micro RNA (miRNA) expression values generated by the Comprehensive Analysis Pipeline for microRNA Sequencing (CAP-miRSeq) 'expression_reports.sh' script. The workflow follows the 'edgeR'-'limma' expression data analysis pipeline providing options for different approaches, such as "pure" 'edgeR', voom or paired samples. The functions in the package generate text files with differential expression lists, optionally annotated with information from 'biomart', expression summary plots as well as several quality control (QC) plots. The main function, diffExpr(), is a convenience wrapper performing all steps automatically based on sensible defaults. Methods are described in Robinson, McCarthy and Smyth (2010) <doi:10.1093/bioinformatics/btp616>, Ritchie et al. (2015) <doi:10.1093/nar/gkv007>, Law et al. (2014) <doi:10.1186/gb-2014-15-2-r29> and Sun et al. (2014) <doi:10.1186/1471-2164-15-423>.

Authors:Vidal Fey [aut, cre], Meeri Pekkarinen [aut], Reija Hieta [aut], Bogdan Iancu [aut], Adrien Janssens [aut]

diffwrap_0.6-3.tar.gz
diffwrap_0.6-3.zip(r-4.7-any)diffwrap_0.6-3.zip(r-4.6-any)
diffwrap_0.6-3.tar.gz(r-4.7-any)diffwrap_0.6-3.tar.gz(r-4.6-any)
diffwrap_0.6-3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
diffwrap/json (API)

# Install 'diffwrap' in R:

install.packages('diffwrap', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

diffwrap_counts - Simulated RNA-Seq read counts for the package examples
diffwrap_samp_info - Sample sheet accompanying the simulated example counts

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

quarto

2.00 score 388 downloads 35 exports 123 dependencies

Last updated from:27e8b17c43. Checks:4 ERROR, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel	ERROR	385
source / vignettes	OK	297
linux-release	ERROR	340
windows-devel	ERROR	288
windows-release	ERROR	277
wasm-release	OK	206

Exports:%>%diff_expr_3d_scatterplot diff_expr_biomart diff_expr_dendro_plot diff_expr_extract_contrasts diff_expr_filter_counts diff_expr_fit diff_expr_get_samp_info diff_expr_ggplot_mds diff_expr_ma_plot diff_expr_make_contrasts diff_expr_make_design diff_expr_mds_plot diff_expr_PCA diff_expr_PCA_ggbiplot diff_expr_PCA_ggplot diff_expr_pseudo_counts diff_expr_pval_hist_plot diff_expr_QC_plots diff_expr_read_counts diff_expr_volcano_plot diffExpr diffr_expr_generate_cleaned_de_table_output diffr_pheatmap diffr_venn ggbiplot.n pheatmap_plots plot_enrichment_network prepare_scale_for_legend prepare_volcano_of_given_property run_clusterProfiler_GO run_clusterProfiler_KEGG run_gprofiler run.topGO runEnrichmentAnalyses

Dependencies:admisc AnnotationDbi askpass assertthat backports base64enc Biobase BiocBaseUtils BiocFileCache BiocGenerics biomaRt Biostrings bit bit64 blob bslib cachem checkmate cli cluster colorspace convertid cpp11 crayon curl data.table DBI dbplyr digest dplyr edgeR evaluate expm farver fastmap filelock fontawesome foreign formatR Formula fs futile.logger futile.options generics ggplot2 ggrepel glue gridExtra gtable highr Hmisc hms htmlTable htmltools htmlwidgets httr httr2 IRanges isoband jquerylib jsonlite KEGGREST knitr labeling lambda.r lattice lifecycle limma locfit ltm magrittr MASS Matrix memoise mime msm mvtnorm nnet openssl openxlsx pheatmap pillar pkgconfig plyr png polycor prettyunits progress purrr R6 rappdirs RColorBrewer Rcpp rlang rmarkdown rpart RSQLite rstudioapi S4Vectors S7 sass scales Seqinfo statmod stringi stringr survival sys tibble tidyr tidyselect tinytex utf8 vctrs venn VennDiagram viridisLite withr xfun xml2 XVector yaml zip

Differential expression analysis with diffwrap

Rendered fromdiffwrap-vignette.qmdusingquarto::html

Last update: 2026-08-30
Started: 2026-08-30

Help page	Topics
Function to create a correlogram pheatmap, i.e., a plot to check randomness in the data set.	correlogram_pheatmap
Function to generate a 3D scatterplot	diff_expr_3d_scatterplot
Function to retrieve additional information from biomart	diff_expr_biomart
Function to generate dendrogram plots based on hierarchical clustering	diff_expr_dendro_plot
Function to extract contrasts and generate top tables and plots	diff_expr_extract_contrasts
Function to filter counts	diff_expr_filter_counts
Function to compute linear model fit and optionally apply 'voom' beforehand	diff_expr_fit
Function to standardize samp.info sample information data frame	diff_expr_get_samp_info
Function to generate a MDS plot using `ggplot2`	diff_expr_ggplot_mds
Function to generate a M-A plot using `ggplot2`	diff_expr_ma_plot
Function to make contrast matrix	diff_expr_make_contrasts
Function to create design matrix	diff_expr_make_design
Wrapper around `limma::plotMDS` to generate a MDS plot	diff_expr_mds_plot
Function to do PCA using `stats::prcomp`	diff_expr_PCA
Function to generate a PCA biplot using `ggbiplot.n`, a version of `ggbiplot` from https://github.com/vqv/ggbiplot.	diff_expr_PCA_ggbiplot
Function to generate an ordinary two-dimensional PCA plot using `ggplot2`	diff_expr_PCA_ggplot
Function to calculate pseudo counts representing batch-corrected normalised but untransformed values	diff_expr_pseudo_counts
Function to generate a histogram of the P-Value distribution	diff_expr_pval_hist_plot
Main wrapper function for QC plots	diff_expr_QC_plots
Function to read counts as produced by htseq-count	diff_expr_read_counts
Function to generate a Volcano plot using `ggplot2`	diff_expr_volcano_plot
Main wrapper for executing the entire pipeline from reading in expression data such as count files to producing text files and graphs	diffExpr
Helper function to generate an output table with only most relevant columns	diffr_expr_generate_cleaned_de_table_output
Function to create a heatmap from differential gene expression values	diffr_pheatmap
Function to produce a Venn diagram of differentially expressed gene tables	diffr_venn
Differential expression analysis of RNA-Seq data	diffwrap
Simulated RNA-Seq read counts for the package examples	diffwrap_counts
Sample sheet accompanying the simulated example counts	diffwrap_samp_info
Helper function for formatting the gene ID column of enrichment data frame.	format_ensembl_ids_annotated_to_term
Function to define breaks to be used for changing the palette of the heatmap.	get_hm_breaks
Function to compute colour palettes to be used in the heatmap.	get_hm_colors
Make a biplot of PCA output data using ggplot2.	ggbiplot.n
Function to create the annotation colour list used in the heatmap	make_pheatmap_anno_color
Function to generate heatmap of gene expression values	pheatmap_plots
Function for making network visualisation based on enrichment result, DE gene table and thresholding. Can take the input tables either as data frames or Excel files	plot_enrichment_network
Helper function for enrichment visualisations: prepare plot legend y coordinates and labels	prepare_scale_for_legend
Helper function that returns a volcano plot.	prepare_volcano_of_given_property
Function to define quantile breaks to be used for changing the palette of the heatmap.	quantile_breaks
Function which reorders the levels of a column of a data frame specified as a factor	reorderFactors
Runs clusterProfiler GO enrichment function for a DEG list or for a ranked gene list.	run_clusterProfiler_GO
Runs clusterProfiler KEGG enrichment function for a DEG list or for a ranked gene list.	run_clusterProfiler_KEGG
Runs gprofiler function for a DEG list or for a ranked gene list.	run_gprofiler
Function to run GO term enrichment analysis using the 'topGO' package.	run.topGO
Wrapper for executing various enrichment analyses	runEnrichmentAnalyses

Package: diffwrap 0.6-3

diffwrap: Differential Expression Analysis of RNA-Seq Data

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