A large amount of multi-species functional genomic data from high-throughput assays (including transcriptional regulation, chromatin states, and nuclear genome organization) are becoming available to help understand the molecular mechanisms for phenotypic diversity across species. However, continuous-trait probabilistic models, which are key to such comparative analysis, remain under-explored. In this talk I will mainly introduce a new model, called phylogenetic hidden Markov Gaussian processes (Phylo-HMGP), to simultaneously infer heterogeneous evolutionary states of functional genomic features in a genome-wide manner. We applied Phylo-HMGP to analyze a new cross-species DNA replication timing (RT) dataset from the same cell type in five primate species and revealed genomic regions with distinct evolutionary patterns of RT. Our method provides a generic framework for comparative analysis of multi-species continuous functional genomic signals to discover changes of gene regulation and genome organization.
Jian Ma is currently an Associate Professor (with tenure) in the School of Computer Science at Carnegie Mellon University. He is a faculty in the Computational Biology Department with affiliated appointment in the Machine Learning Department at CMU. Prior to joining CMU in January 2016, he was an Associate Professor with tenure at the University of Illinois at Urbana-Champaign. The main research focus of his group is to develop algorithms to better understand the organization and function of the human genome.