DOI: 10.18129/B9.bioc.dearseq    

Differential Expression Analysis for RNA-seq data through a robust variance component test

Bioconductor version: Release (3.14)

Differential Expression Analysis 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 repeated or longitudinal data. Methods are detailed in: i) Agniel D & Hejblum BP (2017) Variance component score test for time-course gene set analysis of longitudinal RNA-seq data, Biostatistics, 18(4):589-604 ; and ii) Gauthier M, Agniel D, ThiƩbaut R & Hejblum BP (2020) dearseq: a variance component score test for RNA-Seq differential analysis that effectively controls the false discovery rate, NAR Genomics and Bioinformatics, 2(4):lqaa093.

Author: Denis Agniel [aut], Boris P. Hejblum [aut, cre], Marine Gauthier [aut]

Maintainer: Boris P. Hejblum <boris.hejblum at>

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biocViews BiomedicalInformatics, CellBiology, DNASeq, DifferentialExpression, GeneExpression, GeneSetEnrichment, Genetics, ImmunoOncology, KEGG, RNASeq, Regression, Sequencing, Software, SystemsBiology, TimeCourse, Transcription, Transcriptomics
Version 1.6.0
In Bioconductor since BioC 3.11 (R-4.0) (1.5 years)
License GPL-2 | file LICENSE
Depends R (>= 3.6.0)
Imports ggplot2, KernSmooth, matrixStats, methods, patchwork, parallel, pbapply, stats, statmod, survey, viridisLite
Suggests Biobase, BiocManager, BiocSet, edgeR, DESeq2, GEOquery, GSA, knitr, limma, readxl, rmarkdown, S4Vectors, SummarizedExperiment, testthat, covr
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