MersV1, Main, Exploration, bibRecord, 000D76

Gerbil: a fast and memory-efficient k-mer counter with GPU-support

Identifieur interne : 000D76 ( Main/Exploration ); précédent : 000D75; suivant : 000D77

Gerbil: a fast and memory-efficient k-mer counter with GPU-support

Auteurs : Marius Erbert ; Steffen Rechner ; Matthias Müller-Hannemann

Source :

Algorithms for Molecular Biology : AMB [ 1748-7188 ] ; 2017.

RBID : PMC:5374613

Abstract

Background

A basic task in bioinformatics is the counting of k-mers in genome sequences. Existing k-mer counting tools are most often optimized for small k < 32 and suffer from excessive memory resource consumption or degrading performance for large k. However, given the technology trend towards long reads of next-generation sequencers, support for large k becomes increasingly important.

Results

We present the open source k-mer counting software Gerbil that has been designed for the efficient counting of k-mers for k ≥ 32. Our software is the result of an intensive process of algorithm engineering. It implements a two-step approach. In the first step, genome reads are loaded from disk and redistributed to temporary files. In a second step, the k-mers of each temporary file are counted via a hash table approach. In addition to its basic functionality, Gerbil can optionally use GPUs to accelerate the counting step. In a set of experiments with real-world genome data sets, we show that Gerbil is able to efficiently support both small and large k.

Conclusions

While Gerbil’s performance is comparable to existing state-of-the-art open source k-mer counting tools for small k < 32, it vastly outperforms its competitors for large k, thereby enabling new applications which require large values of k.

Electronic supplementary material

The online version of this article (doi:10.1186/s13015-017-0097-9) contains supplementary material, which is available to authorized users.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374613

DOI: 10.1186/s13015-017-0097-9
PubMed: 28373894
PubMed Central: 5374613

Affiliations:

Le document en format XML

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<p>A basic task in bioinformatics is the counting of <italic>k</italic>
-mers in genome sequences. Existing <italic>k</italic>
-mer counting tools are most often optimized for small <italic>k</italic>
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. However, given the technology trend towards long reads of next-generation sequencers, support for large <italic>k</italic>
 becomes increasingly important.</p>
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<sec><title>Results</title>
<p>We present the open source <italic>k</italic>
-mer counting software <italic>Gerbil</italic>
 that has been designed for the efficient counting of <italic>k</italic>
-mers for <italic>k</italic>
 ≥ 32. Our software is the result of an intensive process of algorithm engineering. It implements a two-step approach. In the first step, genome reads are loaded from disk and redistributed to temporary files. In a second step, the <italic>k</italic>
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 can optionally use GPUs to accelerate the counting step. In a set of experiments with real-world genome data sets, we show that <italic>Gerbil</italic>
 is able to efficiently support both small and large <italic>k</italic>
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-mer counting tools for small <italic>k</italic>
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, thereby enabling new applications which require large values of <italic>k</italic>
.</p>
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Gerbil: a fast and memory-efficient k-mer counter with GPU-support

Gerbil: a fast and memory-efficient k-mer counter with GPU-support

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