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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:2.0
BEGIN:VEVENT
DTSTART:20151117T200000Z
DTEND:20151117T203000Z
LOCATION:18AB
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: Dramatic advances in DNA sequencing technology have made it possible to study microbial environments by direct sequencing of environmental DNA samples. Yet, due to huge volume and high data complexity, current de novo assemblers cannot handle large metagenomic datasets or fail to perform assembly with acceptable quality. This paper presents the first parallel solution for decomposing the metagenomic assembly problem without compromising post-assembly quality. We transform this problem into that of finding weakly connected components in the de Bruijn graph. We propose a novel distributed memory algorithm to identify the connected subgraphs, and present strategies to minimize the communication volume. We demonstrate scalability of our algorithm on soil metagenome dataset with 1.8 billion reads. Our approach achieves a runtime of 22 minutes using 1280 Intel Xeon cores for 421 GB uncompressed FASTQ dataset. Moreover, our solution is generalizable to finding connected components in arbitrary undirected graphs.
SUMMARY:A Parallel Connectivity Algorithm for de Bruijn Graphs in Metagenomic Applications
PRIORITY:3
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