Next-generation VariationHunter: combinatorial algorithms for transposon insertion discovery

• DOI: 10.1093/bioinformatics/btq216
• Publication Date: 2010-06-07T07:28:13Z
• Authors: Fereydoun Hormozd...; Iman Hajirasouliha; Phuong Dao; Faraz Hach; Deniz Yorukoglu; Can Alkan; Evan E. Eichler; S. Cenk Sahinalp
• Keywords: Structural Variation; Scope (computer science)

Abstract Recent years have witnessed an increase in research activity for the detection of structural variants (SVs) and their association to human disease. The advent next-generation sequencing technologies make it possible extend scope variation studies a point previously unimaginable as exemplified by 1000 Genomes Project. Although various computational methods been described SVs, no such algorithm is yet fully capable discovering transposon insertions, very important class SVs study evolution In this article, we provide complete novel formulation discover both loci classes transposons inserted into genomes sequenced with high-throughput technologies. addition, also present ‘conflict resolution’ improvements our earlier combinatorial SV (VariationHunter) taking diploid nature genome consideration. We test algorithms simulated data from Venter (HuRef) are able >85% insertion events precision >90%. demonstrate that conflict resolution (denoted VariationHunter-CR) outperforms current state art (such original VariationHunter, BreakDancer MoDIL) when tested on Yoruba African individual (NA18507). Availability: implementation available at http://compbio.cs.sfu.ca/strvar.htm. Contact: [e-mail]; [e-mail] Supplementary information: Bioinformatics online.