Title
Reprint of "A parallel connectivity algorithm for de Bruijn graphs in metagenomic applications".
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 the 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 the 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 the scalability of our algorithm on a soil metagenome dataset with 1.8 billion reads. Our approach achieves a runtime of 22 min using 1280 Intel Xeon cores for a 421 GB uncompressed FASTQ dataset. Moreover, our solution is generalizable to finding connected components in arbitrary undirected graphs.
Year
DOI
Venue
2017
10.1016/j.parco.2017.09.002
Parallel Computing
Keywords
Field
DocType
Metagenomic assembly,Soil microbiology,de Bruijn graph,Connected component labeling
Computer science,FASTQ format,Parallel computing,Distributed memory,Algorithm,Theoretical computer science,Metagenomics,De Bruijn graph,Connected component,De Bruijn sequence,Xeon,Scalability
Journal
Volume
Issue
ISSN
70
C
0167-8191
Citations 
PageRank 
References 
0
0.34
13
Authors
4
Name
Order
Citations
PageRank
Patrick Flick1314.48
Chirag Jain2297.51
Tony Pan319618.21
Aluru, Srinivas41166122.83