Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads.

ABSTRACT:

Background

RNA sequencing (RNA-seq) is a powerful tool for genome-wide expression profiling of biological samples with the advantage of high-throughput and high resolution. There are many existing algorithms nowadays for quantifying expression levels and detecting differential gene expression, but none of them takes the misaligned reads that are mapped to non-exonic regions into account. We developed a novel algorithm, XBSeq, where a statistical model was established based on the assumption that observed signals are the convolution of true expression signals and sequencing noises. The mapped reads in non-exonic regions are considered as sequencing noises, which follows a Poisson distribution. Given measureable observed and noise signals from RNA-seq data, true expression signals, a

SUBMITTER: Chen HI 

PROVIDER: S-EPMC4474535 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature