Microindel detection in short-read sequence data

• DOI: 10.1093/bioinformatics/btq027
• Publication Date: 2010-02-10T01:33:54Z
• Authors: Peter Krawitz; Christian Rödelsp...; Marten Jäger; Luke Jostins; Sebastian Bauer; Peter N. Robinson
• Keywords: Indel; INDEL Mutation; Sequence (biology); Sanger sequencing

Abstract Motivation: Several recent studies have demonstrated the effectiveness of resequencing and single nucleotide variant (SNV) detection by deep short-read sequencing platforms. While several reliable algorithms are available for automated SNV detection, microindels in data presents a new bioinformatics challenge. Results: We systematically analyzed how mapping tools MAQ, Bowtie, Burrows-Wheeler alignment tool (BWA), Novoalign RazerS perform on simulated datasets that contain indels evaluated affect error rates detection. implemented simple algorithm to compute equivalent indel region eir, which can be used process alignments produced order calling. Using contains indels, we demonstrate works well data: rate (<4 bp) is >90%. Our study provides insights into systematic errors based ungapped short sequence read alignments. Gapped reads reduce this detect data. A comparison with automatically identified ABI Sanger Roche 454 platform indicates microindel from identifies both overlapping distinct indels. Contact: [e-mail]; [e-mail] Supplementary information: at Bioinformatics online.