Pathset graphs: a novel approach for comprehensive utilization of paired reads in genome assembly

Authors:
Son K. Pham;Dmitry Antipov;Alexander Sirotkin;Glenn Tesler;Pavel A. Pevzner;Max A. Alekseyev
Affiliations:
Dept. of Computer Science and Engineering, University of California, San Diego, CA;Dept. of Computer Science and Engineering, University of California, San Diego, CA;Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia;Dept. of Mathematics, University of California, San Diego, CA;Dept. of Computer Science and Engineering, University of California, San Diego, CA, USA and Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia;Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia and Dept. of Computer Science and Engineering, University of South Carolina, Columbia, SC
Venue:
RECOMB'12 Proceedings of the 16th Annual international conference on Research in Computational Molecular Biology
Year:
2012

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Abstract

One of the key advances in genome assembly that has led to a significant improvement in contig lengths has been utilization of paired reads (mate-pairs). While in most assemblers, mate-pair information is used in a post-processing step, the recently proposed Paired de Bruijn Graph (PDBG) approach incorporates the mate-pair information directly in the assembly graph structure. However, the PDBG approach faces difficulties when the variation in the insert sizes is high. To address this problem, we first transform mate-pairs into edge-pair histograms that allow one to better estimate the distance between edges in the assembly graph that represent regions linked by multiple mate-pairs. Further, we combine the ideas of mate-pair transformation and PDBGs to construct new data structures for genome assembly: pathsets and pathset graphs.