Our group develops and contributes to open-source, freely available software for the analysis of high-throughput genomic data. Our code is available through R packages that can be installed from GitHub or the Bioconductor Project. Analysis code to reproduce manuscript results can also be found by clicking on the GitHub logos in the papers list.

developers/authors

• bayesDCA R package to Perform Bayesian Decision Curve Analysis for clinical prediction models and diagnostic tests, available on GitHub

• benchmarkfdr-shiny R/Shiny application for exploring results from “A practical guide to methods controlling false discoveries in computational biology” by Korthauer, Kimes et al. (2019), available on GitHub

• dmrseq Usage Stats R/Bioconductor package for inference for differentially methylated regions (DMRs) from bisulfite sequencing, available on Bioconductor

• scDD Usage Stats R/Bioconductor package for the identification of differentially distributed genes in single-cell RNA-seq, available on Bioconductor

• MADGiC R package for the identification of cancer driver genes by integrating somatic mutation, expression, replication timing, and functional impact, available on GitHub

contributor

• SingleCellExperiment Usage Stats R/Bioconductor package that defines a S4 class and methods for storing and retrieving data from single-cell experiments. Bioconductor

• oligoGames R package for the analysis of tiled massively parallel reporter assays (MPRAs), available on GitHub