A probabilistic framework for aligning paired-end RNA-seq data.

ABSTRACT:

Motivation

The RNA-seq paired-end read (PER) protocol samples transcript fragments longer than the sequencing capability of today's technology by sequencing just the two ends of each fragment. Deep sampling of the transcriptome using the PER protocol presents the opportunity to reconstruct the unsequenced portion of each transcript fragment using end reads from overlapping PERs, guided by the expected length of the fragment.

Methods

A probabilistic framework is described to predict the alignment to the genome of all PER transcript fragments in a PER dataset. Starting from possible exonic and spliced alignments of all end reads, our method constructs potential splicing paths connecting paired ends. An expectation maximization method assigns likelihood values to all splice jun

SUBMITTER: Hu Y 

PROVIDER: S-EPMC2916723 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature