`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.
<img src="man/figures/variancePartition.png" align="center" alt="" style="padding-left:10px;" />
variancePartition 1.31.1 includes a major rewrite of the backend for better error handling. See [Changelog](news/index.html). Importantly, the new version is compatible with emprical Bayes moderated t-statistics for linear mixed models using `eBayes()`.
#### Latest features from GitHub
#### Stable release from Bioconductor
This is a developmental version. For stable release see [Bioconductor version](http://bioconductor.org/packages/variancePartition/).
For questions about specifying contrasts with dream, see [examples here](https://gist.github.com/GabrielHoffman/aa993222bae4d6b7d1caea2334aedbf7).
See [frequently asked questions](http://bioconductor.org/packages/devel/bioc/vignettes/variancePartition/inst/doc/FAQ.html).
See repo of [examples from the paper](https://github.com/GabrielHoffman/dream_analysis).
### 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](https://reprex.tidyverse.org) to produce a GitHub-ready example that is reproducable from a fresh R session.
Describes extensions of `dream` including empirical Bayes moderated t-statistics for linear mixed models and applications to single cell data
- [Hoffman, et al, biorxiv (2023)](https://doi.org/10.1101/2023.03.17.533005)
Describes `dream` for differential expression:
- [Hoffman and Roussos, Bioinformatics (2021)](https://doi.org/10.1093/bioinformatics/btaa687)
Describes the `variancePartition` package:
- [Hoffman and Schadt, BMC Bioinformatics (2016)](https://doi.org/10.1186/s12859-016-1323-z)