I developed chromVAR, an R package that enables interpretable analysis of sparse epigenomics data from single cell ATAC-seq or lightly sequenced bulk epigenomics data. The method finds sequence motifs or other genomic annotations associated with variation in chrommatin accessibility across cells or samples.
I developed a new method for determining nucleosome positioning using ATAC-seq data. The method takes advantage of the highly structured fragmentation pattern that can be observed around well-positioned nucleosomes. The algorithm is implemented as a python package named NucleoATAC.
I used published in situ hybridization, microarray, and RNA-seq datasets to compare expression patterns of transcription factors during early embryonic development between different species. I show that TF expression appears to follow the hourglass model, in that expression is most similar between species mid-way through embryonic development, although for insects it appears there may be two distinct periods of maximal similarity.