Nonparametric Modeling of Next-Generation Sequencing Data

Ping Ma, University of Illinois at Urbana-Champaign

February 1, 2011 @ 04:00 pm to 05:00 pm

201 Thomas Building

With the rapid development of next-generation sequencing technologies, ChIP-seq and RNA-seq have become popular methods for genome-wide protein-DNA interaction analysis and gene expression analysis respectively. Compared to their hybridization-based counterparts, e.g., ChIP-chip and microarray, ChIP-seq and RNA-seq offer down to a single-base resolution signals. In particular, the two technologies produce tens of millions of short reads in a single run. After mapping these reads to reference genome (or transcripts), researchers get a sequence of read counts. That is, at each nucleotide position, researchers get a count which stands for the number of reads whose mapping starts at that position. Depending on research goals, researchers may opt to either analyze these counts directly or derive other types of data based on these counts to facilitate biological discoveries. In this talk, I will present some nonparametric methods we recently developed in analyzing next-generation sequencing data.