Department of Computer Science
 Rutgers University

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CLEVER: Clique-Enumerating Variant Finder

T. Marshall, I. Costa, S. Canzar, M. Bauer, G. Klau, A. Schliep and A. Schönhuth

2012. Arxiv.

Next-generation sequencing techniques have facilitated a large scale analysis of human genetic varia- tion. Despite the advances in sequencing speeds, the computational discovery of structural variants is not yet standard. It is likely that many variants have remained undiscovered in most sequenced individuals. Here we present a novel internal segment size based approach, which organizes all, including also concordant reads into a read alignment graph where max-cliques represent maximal contradiction-free groups of alignments. A specifically engineered algorithm then enumerates all max-cliques and statis- tically evaluates them for their potential to reflect insertions or deletions (indels). For the first time in the literature, we compare a large range of state-of-the-art approaches using simulated Illumina reads from a fully annotated genome and present various relevant performance statistics. We achieve superior performance rates in particular on indels of sizes 20–100, which have been exposed as a current major challenge in the SV discovery literature and where prior insert size based approaches have limitations. In that size range, we outperform even split read aligners. We achieve good results also on real data where we make a substantial amount of correct predictions as the only tool, which complement the predictions of split-read aligners.