Gerbil: A Fast and Memory-Efficient k-mer Counter with GPU-Support release_3xvtaxvuqrhizfazrhhfcd6ssi

by Marius Erbert, Steffen Rechner, Matthias Müller-Hannemann

Released as a article .

2016  

Abstract

A basic task in bioinformatics is the counting of k-mers in genome strings. The k-mer counting problem is to build a histogram of all substrings of length k in a given genome sequence. We present the open source k-mer counting software Gerbil that has been designed for the efficient counting of k-mers for k≥32. Given the technology trend towards long reads of next-generation sequencers, support for large k becomes increasingly important. While existing k-mer counting tools suffer from excessive memory resource consumption or degrading performance for large k, Gerbil is able to efficiently support large k without much loss of performance. Our software implements a two-disk approach. In the first step, DNA reads are loaded from disk and distributed to temporary files that are stored at a working disk. In a second step, the temporary files are read again, split into k-mers and counted via a hash table approach. In addition, Gerbil can optionally use GPUs to accelerate the counting step. For large k, we outperform state-of-the-art open source k-mer counting tools for large genome data sets.
In text/plain format

Archived Files and Locations

application/pdf  633.0 kB
file_iqjdwwnwnbet7lfc5fe7yz7pem
arxiv.org (repository)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article
Stage   submitted
Date   2016-07-22
Version   v1
Language   en ?
arXiv  1607.06618v1
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 2eb6ec6f-2c80-49d0-940b-231e5457eff8
API URL: JSON