RNA-Seq gene expression estimation with read mapping uncertainty.

ABSTRACT:

Motivation

RNA-Seq is a promising new technology for accurately measuring gene expression levels. Expression estimation with RNA-Seq requires the mapping of relatively short sequencing reads to a reference genome or transcript set. Because reads are generally shorter than transcripts from which they are derived, a single read may map to multiple genes and isoforms, complicating expression analyses. Previous computational methods either discard reads that map to multiple locations or allocate them to genes heuristically.

Results

We present a generative statistical model and associated inference methods that handle read mapping uncertainty in a principled manner. Through simulations parameterized by real RNA-Seq data, we show that our method is more accurate than previous meth

SUBMITTER: Li B 

PROVIDER: S-EPMC2820677 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature