Differential analysis of DNA-seq Data
Bo Hu, Cleveland Clinic
Wednesday, November 17, 2010
3:00 p.m., Weber 223
DNA methylation is an epigenetic modification of human and mammalian genomes, involved in both normal developmental processes and disease states through the modulation of gene expression and the maintenance of genomic structure. Next-generation sequencing technologies have emerged as powerful tools for whole-genome profiling of epigenetic modifications, and there is great interest in strategies for analyzing whole-genome DNA methylation data using high-throughput next-generation sequencer. We propose an integrated statistical and computational approach for analyzing methylation profiles in a multiple comparative study design. The sequencing data are first mapped as multistate probabilities to deconvolute the background and random noises. Differential pattern and regions are then identified with scan statistics. We applied our approach to a colon cancer study with whole-genome methylation profile data generated using MBD-isolated Genome Sequencing (MiGS) with the Illumina Genome Analyzer II. The results are validated using the conventional bisulfite sequencing.