I develop and contribute to open-source, freely available software for the analysis of high-throughput genomic data. My 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 on my GitHub page.

developer/author

• 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