A Bayesian approach for estimating allele-specific expression from RNA-Seq data with diploid genomes.

ABSTRACT:

Background

RNA-sequencing (RNA-Seq) has become a popular tool for transcriptome profiling in mammals. However, accurate estimation of allele-specific expression (ASE) based on alignments of reads to the reference genome is challenging, because it contains only one allele on a mosaic haploid genome. Even with the information of diploid genome sequences, precise alignment of reads to the correct allele is difficult because of the high-similarity between the corresponding allele sequences.

Results

We propose a Bayesian approach to estimate ASE from RNA-Seq data with diploid genome sequences. In the statistical framework, the haploid choice is modeled as a hidden variable and estimated simultaneously with isoform expression levels by variational Bayesian inference. Through the s

SUBMITTER: Nariai N 

PROVIDER: S-EPMC4895278 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature