Towards accurate detection and genotyping of expressed variants from whole transcriptome sequencing data.

ABSTRACT:

Background

Massively parallel transcriptome sequencing (RNA-Seq) is becoming the method of choice for studying functional effects of genetic variability and establishing causal relationships between genetic variants and disease. However, RNA-Seq poses new technical and computational challenges compared to genome sequencing. In particular, mapping transcriptome reads onto the genome is more challenging than mapping genomic reads due to splicing. Furthermore, detection and genotyping of single nucleotide variants (SNVs) requires statistical models that are robust to variability in read coverage due to unequal transcript expression levels.

Results

In this paper we present a strategy to more reliably map transcriptome reads by taking advantage of the availability of both the gen

SUBMITTER: Duitama J 

PROVIDER: S-EPMC3394419 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature