BADGE: a novel Bayesian model for accurate abundance quantification and differential analysis of RNA-Seq data.

ABSTRACT:

Background

Recent advances in RNA sequencing (RNA-Seq) technology have offered unprecedented scope and resolution for transcriptome analysis. However, precise quantification of mRNA abundance and identification of differentially expressed genes are complicated due to biological and technical variations in RNA-Seq data.

Results

We systematically study the variation in count data and dissect the sources of variation into between-sample variation and within-sample variation. A novel Bayesian framework is developed for joint estimate of gene level mRNA abundance and differential state, which models the intrinsic variability in RNA-Seq to improve the estimation. Specifically, a Poisson-Lognormal model is incorporated into the Bayesian framework to model within-sample variation; a

SUBMITTER: Gu J 

PROVIDER: S-EPMC4168709 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature