Package: ROSeq 1.17.0
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.
Authors:
ROSeq_1.17.0.tar.gz
ROSeq_1.17.0.zip(r-4.5)ROSeq_1.17.0.zip(r-4.4)ROSeq_1.17.0.zip(r-4.3)
ROSeq_1.17.0.tgz(r-4.4-any)ROSeq_1.17.0.tgz(r-4.3-any)
ROSeq_1.17.0.tar.gz(r-4.5-noble)ROSeq_1.17.0.tar.gz(r-4.4-noble)
ROSeq_1.17.0.tgz(r-4.4-emscripten)ROSeq_1.17.0.tgz(r-4.3-emscripten)
ROSeq.pdf |ROSeq.html✨
ROSeq/json (API)
NEWS
# Install 'ROSeq' in R: |
install.packages('ROSeq', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/krishan57gupta/roseq/issues
- L_Tung_single - Single cell samples for DE genes analysis
On BioConductor:ROSeq-1.17.0(bioc 3.20)ROSeq-1.16.0(bioc 3.19)
Last updated 2 months agofrom:72d00a4af8
Exports:ROSeqTMMnormalization