Statistical Modeling of Differential Splicing with RNA-Seq

• Activity Number: 476
• Type: Topic Contributed
• Date/Time: Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Hui Jiang*+ and Yang Shi and Julia Salzman
• Companies: University of Michigan and University of Michigan and Stanford University
• Keywords: RNA-seq ; gene expression ; alternative splicing ; likelihood ratio test ; resampling ; multiple testing

Abstract

Alternative splicing is a cell mechanism which is of vital importance to gene regulation and expression in higher eukaryotes and can have significant impact on many diseases. This talk will present a statistical model for detecting differential splicing from high-throughput sequencing data based on a linear Poisson model and hierarchical likelihood ratio test. An early stopping rule for resampling-based multiple testing is used to save the computation. The approach will be demonstrated on both simulated and real data. This talk is based on joint works with Yang Shi and Julia Salzman.