WemIQ: an accurate and robust isoform quantification method for RNA-seq data.

ABSTRACT:

Motivation

The deconvolution of isoform expression from RNA-seq remains challenging because of non-uniform read sampling and subtle differences among isoforms.

Results

We present a weighted-log-likelihood expectation maximization method on isoform quantification (WemIQ). WemIQ integrates an effective bias removal with a weighted expectation maximization (EM) algorithm to distribute reads among isoforms efficiently. The weight represents the oversampling or undersampling of sequence reads and is estimated through a generalized Poisson model without any presumption on the bias sources and formats. WemIQ significantly improves the quantification of isoform and gene expression as well as the derived exon inclusion rates. It provides robust expression estimates across different l

SUBMITTER: Zhang J 

PROVIDER: S-EPMC4380033 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature