RNA-seq driven gene identification

Abstract

The reliable identification of genes is a challenging and crucial part of genome research. Various methods aiming at accurate predictions have evolved that predict genes ab initio on reference sequences or evidence based with help of additional information. With high-throughput RNA-Seq data reflecting currently expressed genes, a particularly meaningful source of information has become commonly available. However, a particular challenge in including RNA-Seq data is the difficult handling of ambiguously mapped reads. Therefore we developed GIIRA, a novel gene finder that is exclusively based on RNA-Seq data and inherently includes ambiguously mapped reads. Evaluation on simulated and real data and comparison with existing methods incorporating RNA-Seq information highlight the accuracy of GIIRA in identifying the expressed genes. Further, we developed a framework to integrate GIIRA and other gene finders to obtain a verified and accurate set of gene predictions.