XSAnno: a framework for building ortholog models in cross-species transcriptome comparisons.

ABSTRACT:

Background

The accurate characterization of RNA transcripts and expression levels across species is critical for understanding transcriptome evolution. As available RNA-seq data accumulate rapidly, there is a great demand for tools that build gene annotations for cross-species RNA-seq analysis. However, prevailing methods of ortholog annotation for RNA-seq analysis between closely-related species do not take inter-species variation in mappability into consideration.

Results

Here we present XSAnno, a computational framework that integrates previous approaches with multiple filters to improve the accuracy of inter-species transcriptome comparisons. The implementation of this approach in comparing RNA-seq data of human, chimpanzee, and rhesus macaque brain transcriptomes has re

SUBMITTER: Zhu Y 

PROVIDER: S-EPMC4035071 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature