This package is for version 3.14 of Bioconductor; for the stable, up-to-date release version, see ROSeq.
Bioconductor version: 3.14
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")
):
To install this package, start R (version "4.1") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("ROSeq")
HTML | R Script | ROSeq |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | DifferentialExpression, GeneExpression, SingleCell, Software |
Version | 1.6.0 |
In Bioconductor since | BioC 3.11 (R-4.0) (2 years) |
License | GPL-3 |
Depends | R (>= 4.0) |
Imports | pbmcapply, edgeR, limma |
LinkingTo | |
Suggests | knitr, rmarkdown, testthat, RUnit, BiocGenerics |
SystemRequirements | |
Enhances | |
URL | https://github.com/krishan57gupta/ROSeq |
BugReports | https://github.com/krishan57gupta/ROSeq/issues |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | ROSeq_1.6.0.tar.gz |
Windows Binary | ROSeq_1.6.0.zip |
macOS 10.13 (High Sierra) | ROSeq_1.6.0.tgz |
Source Repository | git 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/ |
Package Downloads Report | Download Stats |
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