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FSG: Fast String Graph Construction for De Novo Assembly.

Authors :
Bonizzoni, Paola
Vedova, Gianluca Della
Pirola, Yuri
Previtali, Marco
Rizzi, Raffaella
Source :
Journal of Computational Biology. Oct2017, Vol. 24 Issue 10, p953-968. 16p.
Publication Year :
2017

Abstract

The string graph for a collection of next-generation reads is a lossless data representation that is fundamental for de novo assemblers based on the overlap-layout-consensus paradigm. In this article, we explore a novel approach to compute the string graph, based on the FM-index and Burrows and Wheeler Transform. We describe a simple algorithm that uses only the FM-index representation of the collection of reads to construct the string graph, without accessing the input reads. Our algorithm has been integrated into the string graph assembler (SGA) as a standalone module to construct the string graph. The new integrated assembler has been assessed on a standard benchmark, showing that fast string graph (FSG) is significantly faster than SGA while maintaining a moderate use of main memory, and showing practical advantages in running FSG on multiple threads. Moreover, we have studied the effect of coverage rates on the running times. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10665277
Volume :
24
Issue :
10
Database :
Academic Search Index
Journal :
Journal of Computational Biology
Publication Type :
Academic Journal
Accession number :
125580187
Full Text :
https://doi.org/10.1089/cmb.2017.0089