DOI: 10.18129/B9.bioc.variancePartition    

Quantify and interpret divers of variation in multilevel gene expression experiments

Bioconductor version: Release (3.6)

Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables.

Author: Gabriel E. Hoffman

Maintainer: Gabriel E. Hoffman <gabriel.hoffman at>

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PDF R Script 1) Tutorial on using variancePartition
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biocViews GeneExpression, RNASeq, Regression, Software
Version 1.8.1
In Bioconductor since BioC 3.2 (R-3.2) (2.5 years)
License GPL (>= 2)
Depends ggplot2, foreach, Biobase, methods
Imports MASS, pbkrtest (>= 0.4-4), iterators, splines, colorRamps, gplots, reshape2, lme4 (>= 1.1-10), doParallel, limma, grDevices, graphics, utils, stats
Suggests edgeR, dendextend, tximport, tximportData, ballgown, DESeq2, readr, knitr, BiocStyle
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