zktuong/variancePartition

Quantify and interpret divers of variation in multilevel gene expression experiments

variancePartition quantifies and interprets multiple sources of biological and technical variation in gene expression experiments. The package a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. The dream() function performs differential expression analysis for datasets with repeated measures or high dimensional batch effects.

Tutorial on variance partitioning

Install from GitHub

devtools::install_github("DiseaseNeurogenomics/variancePartition")

Notes

This is a developmental version. For stable release see Bioconductor version.

For questions about specifying contrasts with dream, see examples here.

See frequently asked questions.

See repo of examples from the paper.

Reporting bugs

Please help speed up bug fixes by providing a 'minimal reproducible example' that starts with a new R session. I recommend the reprex package to produce a GitHub-ready example that is reproducable from a fresh R session.

References

Manuscript describing dream for differential expression:

• Hoffman and Roussos, Bioinformatics (2021)

Manuscript describing the variancePartition package:

• Hoffman and Schadt, BMC Bioinformatics (2016)