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Motivation: High-throughput sequencing enables expression analysis at the level of individual transcripts. The analysis of transcriptome expression levels and differential expression 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 BitSeq (Bayesian Inference of Transcripts from Sequencing data), a Bayesian approach fordoi:10.1093/bioinformatics/bts260 pmid:22563066 pmcid:PMC3381971 fatcat:awexp7n36fcbhgnkb5f2cht2ni