Computational challenges in next-generation genomics

Next-generation sequencing (NGS) technology allows us to peer inside the cell in exquisite detail, revealing new insights into biology, evolution, and disease that would have been impossible to find just a few years ago. The enormous volumes of data produced by NGS experiments present many computational challenges that we are working to address. In this talk, I will discuss solutions to two basic alignment problems: (1) mapping sequences onto the human genome at very high speed, and (2) mapping and assembling transcripts from RNA-seq experiments. I will also discuss some of the problems that can arise during alignment and how these can lead to mistaken conclusions about genetic variation and gene expression. My group has developed algorithms to solve each of these problems, including the widely-used Bowtie and Bowtie2 programs for fast alignment and the TopHat and Cufflinks programs for assembly and quantification of genes in transcriptome sequencing (RNA-seq) experiments. This talk describes joint work with current and former lab members including Ben Langmead, Cole Trapnell, Daehwan Kim, and Geo Pertea; and with collaborators including Mihai Pop and Lior Pachter.