Transcriptome Assembly: Computational Challenges of Next-Generation Sequence Data

Steven L. Salzberg, Ph.D.
Bloomberg Distinguished Professor of Biomedical Engineering, Computer Science, and Biostatistics
Directory, Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine
Johns Hopkins University School of Medicine
http://salzberg-lab.org

Next-generation sequencing technology allows us to peer inside the cell in exquisite detail, revealing new aspects of biology, evolution, and disease that would have been impossible to discover 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 recent years, scientists in my lab have developed multiple systems for sequence analysis, including the widely-used Bowtie, TopHat and Cufflinks programs for alignment and assembly of transcipts from RNA-seq data. In this talk, I will discuss two new systems: (1) the HISAT system for spliced aligment of NGS reads, a successor to TopHat; and (2) the StringTie program for assembly and quantitation of RNA-seq data, a successor to Cufflinks.
This talk describes joint work with Daehwan Kim, Ph.D. and Mihaela Pertea, Ph.D.