RNA-Seq alignment to individualized genomes improves transcript abundance estimates in multiparent populations.

ABSTRACT: Massively parallel RNA sequencing (RNA-seq) has yielded a wealth of new insights into transcriptional regulation. A first step in the analysis of RNA-seq data is the alignment of short sequence reads to a common reference genome or transcriptome. Genetic variants that distinguish individual genomes from the reference sequence can cause reads to be misaligned, resulting in biased estimates of transcript abundance. Fine-tuning of read alignment algorithms does not correct this problem. We have developed Seqnature software to construct individualized diploid genomes and transcriptomes for multiparent populations and have implemented a complete analysis pipeline that incorporates other existing software tools. We demonstrate in simulated and real data sets that alignment to individualized tran

SUBMITTER: Munger SC 

PROVIDER: S-EPMC4174954 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature