Adjusting for Transcript Length Bias in RNA-seq to Improve Downstream Analyses

• Activity Number: 125
• Type: Contributed
• Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Justin Wade Davis*+
• Companies: University of Missouri
• Keywords: Gene Ontology ; Next Generation Sequencing ; Gene List ; Transcript Length Bias ; RNA-Seq

Abstract

Next generation sequencing (NGS) has taken the scientific community by storm due to its high-throughput, flexibility, and lower costs. One application of NGS, termed RNA-Seq, is positioned to displace microarrays for differential gene expression analysis. However, Oshlack and Wakefield (2009) showed that there is transcript length bias (TLB) inherent to RNA-Seq which can't be attenuated via statistical means or through changes in the technology. TLB confounds current methodology used in downstream analysis, such as pathway or gene ontology (GO) analyses. In this talk, we focus on the impact TLB has on traditional systems biology type analyses, and propose a solution to account for TLB in order to yield less biased downstream results.