tcgsaseq: Time-Course Gene Set Analysis for RNA-Seq Data

Analyze RNA-seq data with variance component score test accounting for data heteroscedasticity through precision weights. Perform both gene-wise and gene set analyses, and can deal with longitudinal data. Method is detailed in: Agniel & Hejblum (2017) <doi:10.1093/biostatistics/kxx005>, Variance component score test for time-course gene set analysis of longitudinal RNA-seq data, Biostatistics, 18(4):589-604.

Version: 2.0.5
Depends: R (≥ 3.0.2)
Imports: CompQuadForm, ggplot2, graphics, GSA, KernSmooth, parallel, pbapply, stats, statmod, utils
Suggests: limma, edgeR, DESeq2, S4Vectors, knitr, rmarkdown, testthat, covr
Published: 2020-09-10
Author: Denis Agniel [aut], Boris P. Hejblum [aut, cre], Marine Gauthier [aut]
Maintainer: Boris P. Hejblum <boris.hejblum at u-bordeaux.fr>
BugReports: https://github.com/denisagniel/tcgsaseq/issues
License: GPL-2 | file LICENSE
NeedsCompilation: no
Citation: tcgsaseq citation info
Materials: README NEWS
CRAN checks: tcgsaseq results

Downloads:

Reference manual: tcgsaseq.pdf
Package source: tcgsaseq_2.0.5.tar.gz
Windows binaries: r-devel: tcgsaseq_2.0.5.zip, r-release: tcgsaseq_2.0.5.zip, r-oldrel: tcgsaseq_2.0.5.zip
macOS binaries: r-release: tcgsaseq_2.0.5.tgz, r-oldrel: tcgsaseq_2.0.5.tgz
Old sources: tcgsaseq archive

Reverse dependencies:

Reverse suggests: TcGSA

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