Accelerating metagenomic read classification on CUDA-enabled GPUs
Identifieur interne : 001903 ( Ncbi/Curation ); précédent : 001902; suivant : 001904Accelerating metagenomic read classification on CUDA-enabled GPUs
Auteurs : Robin Kobus [Allemagne] ; Christian Hundt [Allemagne] ; André Müller [Allemagne] ; Bertil Schmidt [Allemagne]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2017.
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Abstract
Metagenomic sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification; i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes software tools for fast and accurate metagenomic read classification are urgently needed.
We present cuCLARK, a read-level classifier for CUDA-enabled GPUs, based on the fast and accurate classification of metagenomic sequences using reduced
cuCLARK can perform metagenomic read classification at superior speeds on CUDA-enabled GPUs. It is free software licensed under GPL and can be downloaded at
Url:
DOI: 10.1186/s12859-016-1434-6
PubMed: 28049411
PubMed Central: 5209836
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PMC:5209836Le document en format XML
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<author><name sortKey="Kobus, Robin" sort="Kobus, Robin" uniqKey="Kobus R" first="Robin" last="Kobus">Robin Kobus</name>
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<author><name sortKey="Schmidt, Bertil" sort="Schmidt, Bertil" uniqKey="Schmidt B" first="Bertil" last="Schmidt">Bertil Schmidt</name>
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<series><title level="j">BMC Bioinformatics</title>
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<term>Internet</term>
<term>Metagenomics</term>
<term>Sequence Analysis, DNA</term>
<term>User-Computer Interface</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de séquence d'ADN</term>
<term>Humains</term>
<term>Interface utilisateur</term>
<term>Internet</term>
<term>Métagénomique</term>
<term>Séquençage nucléotidique à haut débit</term>
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<term>Internet</term>
<term>Metagenomics</term>
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<term>User-Computer Interface</term>
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<term>Humains</term>
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>Metagenomic sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification; i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes software tools for fast and accurate metagenomic read classification are urgently needed.</p>
</sec>
<sec><title>Results</title>
<p>We present cuCLARK, a read-level classifier for CUDA-enabled GPUs, based on the fast and accurate classification of metagenomic sequences using reduced <italic>k</italic>
-mers (CLARK) method. Using the processing power of a single Titan X GPU, cuCLARK can reach classification speeds of up to 50 million reads per minute. Corresponding speedups for species- (genus-)level classification range between 3.2 and 6.6 (3.7 and 6.4) compared to multi-threaded CLARK executed on a 16-core Xeon CPU workstation.</p>
</sec>
<sec><title>Conclusion</title>
<p>cuCLARK can perform metagenomic read classification at superior speeds on CUDA-enabled GPUs. It is free software licensed under GPL and can be downloaded at <ext-link ext-link-type="uri" xlink:href="https://github.com/funatiq/cuclark">https://github.com/funatiq/cuclark</ext-link>
free of charge.</p>
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