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ROSeq

This is the released version of ROSeq; for the devel version, see ROSeq.

All versions 3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11

Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-Seq data


Bioconductor version: Release (3.23)

ROSeq - A rank based approach to modeling gene expression with filtered and normalized read count matrix. ROSeq takes filtered and normalized read matrix and cell-annotation/condition as input and determines the differentially expressed genes between the contrasting groups of single cells. One of the input parameters is the number of cores to be used.

Author: Krishan Gupta [aut, cre], Manan Lalit [aut], Aditya Biswas [aut], Abhik Ghosh [aut], Debarka Sengupta [aut]

Maintainer: Krishan Gupta <krishang at iiitd.ac.in>

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

Krishan Gupta, Manan Lalit, Aditya Biswas, Abhik Ghosh, Debarka Sengupta. ROSeq: Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-Seq data. doi:10.18129/B9.bioc.ROSeq, R package version 1.24.0, https://bioconductor.org/packages/ROSeq.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ROSeq")

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

Documentation

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

browseVignettes("ROSeq")
ROSeq HTML R Script
Reference ManualPDF
NEWSText
LICENSEText

Details

biocViews DifferentialExpression, GeneExpression, SingleCell, Software
Version1.24.0
In Bioconductor sinceBioC 3.11 (R-4.0) (6.5 years)
License GPL-3
Depends R (>= 4.0)
Imports pbmcapply, edgeR, limma
System Requirements
URLhttps://github.com/krishan57gupta/ROSeq
Bug Reportshttps://github.com/krishan57gupta/ROSeq/issues
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Suggests knitr, rmarkdown, testthat, RUnit, BiocGenerics
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package ROSeq_1.24.0.tar.gz
Windows Binary (x86_64) ROSeq_1.24.0.zip (64-bit only)
macOS Binary (big-sur-x86_64) ROSeq_1.24.0.tgz
macOS Binary (sonoma-arm64) ROSeq_1.24.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/ROSeq
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/ROSeq
Package Short Url https://bioconductor.org/packages/ROSeq/
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