DOI: 10.18129/B9.bioc.variancePartition    

This package is for version 3.7 of Bioconductor; for the stable, up-to-date release version, see variancePartition.

Quantify and interpret divers of variation in multilevel gene expression experiments

Bioconductor version: 3.7

Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. Includes dream differential expression analysis for repeated measures.

Author: Gabriel E. Hoffman

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

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PDF R Script 1) Tutorial on using variancePartition
PDF R Script 2) Additional visualizations
PDF R Script 3) Theory and practice of random effects
HTML R Script 4) Differential expression testing with repeated measures designs
PDF   Reference Manual
Text   NEWS


biocViews BatchEffect, DifferentialExpression, GeneExpression, Normalization, Preprocessing, QualityControl, RNASeq, Regression, Software, Transcription
Version 1.10.4
In Bioconductor since BioC 3.2 (R-3.2) (3 years)
License GPL (>= 2)
Depends R (>= 3.0.0), ggplot2, limma, foreach, scales, Biobase, methods
Imports MASS, pbkrtest (>= 0.4-4), lmerTest, iterators, splines, colorRamps, gplots, reshape2, lme4 (>= 1.1-10), doParallel, grDevices, graphics, utils, stats
Suggests BiocStyle, knitr, pander, rmarkdown, edgeR, dendextend, tximport, tximportData, ballgown, DESeq2, RUnit, BiocGenerics, r2glmm, readr
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