bioconductor-roseq
Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-Seq data
Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-Seq data
To install this package, run one of the following:
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.
Summary
Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-Seq data
Last Updated
Dec 15, 2024 at 07:52
License
GPL-3
Total Downloads
15.5K
Supported Platforms