Our laboratory is actively developing novel algorithms to improve integration of multi-omics data, high-dimensional flow cytometry, single cell sequencing data, microbiome data and genetic diversity information to improve analysis of these complex data sets.
We have previously developed a tool called MMARGE (Motif Mutation Analysis for Regulatory Genomic Elements) that allows the integration of RNA-seq, ChIP-seq, ATAC-seq and HiC data sets with natural genetic variation information from different mouse strains and patient data. We strive to develop powerful tools that are easy to use, but flexible to accommodate the usage of many different data types.