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GIIRA--RNA-Seq driven gene finding incorporating ambiguous reads.
Zickmann, Franziska; Lindner, Martin S; Renard, Bernhard Y.
Affiliation
  • Zickmann F; Research Group Bioinformatics (NG4), Robert Koch-Institute, Nordufer 20, 13353 Berlin, Germany.
Bioinformatics ; 30(5): 606-13, 2014 Mar 01.
Article in En | MEDLINE | ID: mdl-24123675
ABSTRACT
MOTIVATION The reliable identification of genes is a major challenge in genome research, as further analysis depends on the correctness of this initial step. With high-throughput RNA-Seq data reflecting currently expressed genes, a particularly meaningful source of information has become commonly available for gene finding. However, practical application in automated gene identification is still not the standard case. A particular challenge in including RNA-Seq data is the difficult handling of ambiguously mapped reads.

RESULTS:

We present GIIRA (Gene Identification Incorporating RNA-Seq data and Ambiguous reads), a novel prokaryotic and eukaryotic gene finder that is exclusively based on a RNA-Seq mapping and inherently includes ambiguously mapped reads. GIIRA extracts candidate regions supported by a sufficient number of mappings and reassigns ambiguous reads to their most likely origin using a maximum-flow approach. This avoids the exclusion of genes that are predominantly supported by ambiguous mappings. 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. AVAILABILITY AND IMPLEMENTATION GIIRA is implemented in Java and is available from https//sourceforge.net/projects/giira/.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sequence Analysis, RNA / Gene Expression Profiling / Genes Type of study: Diagnostic_studies / Prognostic_studies Limits: Animals / Humans Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2014 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sequence Analysis, RNA / Gene Expression Profiling / Genes Type of study: Diagnostic_studies / Prognostic_studies Limits: Animals / Humans Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2014 Document type: Article Affiliation country: