Identifying differentially expressed transcripts from RNA-seq data with biological variation.

Peter Glaus, Antti Honkela, Magnus Rattray

Abstract: High-throughput sequencing enables expression analysis at the level of individual transcripts. The analysis of transcriptome expression levels and differential expression (DE) estimation requires a probabilistic approach to properly account for ambiguity caused by shared exons and finite read sampling as well as the intrinsic biological variance of transcript expression.