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Abstract:
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Comparative genomics has gained increasing popularity in genomic research thanks to the development of high-throughput technologies including microarray and next-generation sequencing that have generated numerous genomic data. Many important scientific questions are related to understanding the conservation and differentiation of biological processes in different species. In this talk, I will introduce two testing based measures: TROM (Transcriptome Overlap Measure) and EPOM (Epigenome Overlap Measure), for comparing transcriptomes and epigenomes within or between different species. In contrast to classical correlation analyses, these two measures provide a different perspective to interpret the similarity of transcriptomes and epigenomes. Specifically, they are based on 1) identified associated genes or intergenic regions that capture transcriptomic or epigenomic characteristics of biological samples and 2) an overlap test. We use simulation and real data studies to demonstrate that these testing based measures are more powerful in identifying similar transcriptomes or epigenomes and more robust to data noise than Pearson and Spearman correlations.
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