Improved transcript isoform discovery using ORF graphs

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Item Type:	Article
Title:	Improved transcript isoform discovery using ORF graphs
Creators Name:	Majoros, W.H., Lebeck, N., Ohler, U. and Li, S.
Abstract:	MOTIVATION: High-throughput sequencing of RNA in vivo facilitates many applications, not the least of which is the cataloging of variant splice isoforms of protein-coding messenger RNAs. While many solutions have been proposed for reconstructing putative isoforms from deep sequencing data, these generally take as their substrate the collective alignment structure of RNA-seq reads and ignore the biological signals present in the actual nucleotide sequence. The majority of these solutions are graph-theoretic, relying on a splice graph representing the splicing patterns and exon expression levels indicated by the spliced-alignment process. RESULTS: We show how to augment splice graphs with additional information reflecting the biology of transcription, splicing, and translation, to produce what we call an ORF (open reading frame) graph. We then show how ORF graphs can be used to produce isoform predictions with higher accuracy than current state-of-the-art approaches. AVAILABILITY AND IMPLEMENTATION: RSVP is available as C++ source code under an open-source licence: http://ohlerlab.mdc-berlin.de/software/RSVP/.
Keywords:	Arabidopsis, Exons, High-Throughput Nucleotide Sequencing, Open Reading Frames, RNA Isoforms, RNA Sequence Analysis, RNA Splicing, Software
Source:	Bioinformatics
ISSN:	1367-4803
Publisher:	Oxford University Press
Volume:	30
Number:	14
Page Range:	1958-1964
Date:	15 July 2014
Official Publication:	https://doi.org/10.1093/bioinformatics/btu160
PubMed:	View item in PubMed

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