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This is the development version of broadSeq; to use it, please install the devel version of Bioconductor.

broadSeq : for streamlined exploration of RNA-seq data

Bioconductor version: Development (3.20)

This package helps user to do easily RNA-seq data analysis with multiple methods (usually which needs many different input formats). Here the user will provid the expression data as a SummarizedExperiment object and will get results from different methods. It will help user to quickly evaluate different methods.

Author: Rishi Das Roy [aut, cre]

Maintainer: Rishi Das Roy <rishi.dasroy at>

Citation (from within R, enter citation("broadSeq")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Using broadSeq to analyze RNA-seq data HTML R Script
Reference Manual PDF


biocViews Coverage, DifferentialExpression, GO, GeneExpression, GeneSetEnrichment, RNASeq, Sequencing, Software, Transcriptomics
Version 0.99.3
In Bioconductor since BioC 3.20 (R-4.4)
License MIT + file LICENSE
Depends dplyr, ggpubr, SummarizedExperiment
Imports BiocStyle, DELocal, EBSeq(>= 1.38.0), DESeq2(>= 1.38.2), NOISeq, forcats (>= 1.0.0), genefilter, ggplot2, ggplotify, plyr, clusterProfiler(>= 4.8.2), pheatmap, sechm(>= 1.6.0), stringr, purrr (>= 0.3.5), edgeR(>= 3.40.1)
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Suggests knitr, limma(>= 3.54.0), rmarkdown, stats (>= 4.2.2), samr
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Follow Installation instructions to use this package in your R session.

Source Package broadSeq_0.99.3.tar.gz
Windows Binary
macOS Binary (x86_64) broadSeq_0.99.3.tgz
macOS Binary (arm64) broadSeq_0.99.3.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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