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Article

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

Bioinformatics (Oxford, England) - 1 Jul 2012

Glaus Peter, Honkela Antti, Rattray Magnus

Abstract excerpt

MOTIVATION: 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. RESULTS: We present Bayesian...

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PMID: 22563066
DOI: 10.1093/bioinformatics/bts260
PMCID: PMC3381971

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