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

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.

Package details

AuthorKrishan Gupta [aut, cre], Manan Lalit [aut], Aditya Biswas [aut], Abhik Ghosh [aut], Debarka Sengupta [aut]
Bioconductor views DifferentialExpression GeneExpression SingleCell
MaintainerKrishan Gupta <>
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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ROSeq documentation built on Feb. 18, 2021, 2 a.m.