<br> `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;" /> <br> #### [Tutorial on variance partitioning](https://hoffmg01.hpc.mssm.edu/software/variancePartition/variancePartition.pdf) <br> ### Install from GitHub ```r devtools::install_github("DiseaseNeurogenomics/variancePartition") ``` ### Notes 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. ## References Manuscript describing `dream` for differential expression: - [Hoffman and Roussos, Bioinformatics (2021)](https://doi.org/10.1093/bioinformatics/btaa687) Manuscript describing the `variancePartition` package: - [Hoffman and Schadt, BMC Bioinformatics (2016)](https://doi.org/10.1186/s12859-016-1323-z)