MersV1, PubMed, Corpus, bibRecord, 001643

CoMeta: classification of metagenomes using k-mers.

Identifieur interne : 001643 ( PubMed/Corpus ); précédent : 001642; suivant : 001644

CoMeta: classification of metagenomes using k-mers.

Auteurs : Jolanta Kawulok ; Sebastian Deorowicz

Source :

PloS one [ 1932-6203 ] ; 2015.

RBID : pubmed:25884504

English descriptors

KwdEn :
- Algorithms, Databases, Genetic, Internet, Metagenomics (methods), Sequence Analysis, DNA, User-Computer Interface.
MESH :
- methods : Metagenomics.
- Algorithms, Databases, Genetic, Internet, Sequence Analysis, DNA, User-Computer Interface.

Abstract

Nowadays, the study of environmental samples has been developing rapidly. Characterization of the environment composition broadens the knowledge about the relationship between species composition and environmental conditions. An important element of extracting the knowledge of the sample composition is to compare the extracted fragments of DNA with sequences derived from known organisms. In the presented paper, we introduce an algorithm called CoMeta (Classification of metagenomes), which assigns a query read (a DNA fragment) into one of the groups previously prepared by the user. Typically, this is one of the taxonomic rank (e.g., phylum, genus), however prepared groups may contain sequences having various functions. In CoMeta, we used the exact method for read classification using short subsequences (k-mers) and fast program for indexing large set of k-mers. In contrast to the most popular methods based on BLAST, where the query is compared with each reference sequence, we begin the classification from the top of the taxonomy tree to reduce the number of comparisons. The presented experimental study confirms that CoMeta outperforms other programs used in this context. CoMeta is available at https://github.com/jkawulok/cometa under a free GNU GPL 2 license.

DOI: 10.1371/journal.pone.0121453
PubMed: 25884504

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pubmed:25884504

Le document en format XML

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<front><div type="abstract" xml:lang="en">Nowadays, the study of environmental samples has been developing rapidly. Characterization of the environment composition broadens the knowledge about the relationship between species composition and environmental conditions. An important element of extracting the knowledge of the sample composition is to compare the extracted fragments of DNA with sequences derived from known organisms. In the presented paper, we introduce an algorithm called CoMeta (Classification of metagenomes), which assigns a query read (a DNA fragment) into one of the groups previously prepared by the user. Typically, this is one of the taxonomic rank (e.g., phylum, genus), however prepared groups may contain sequences having various functions. In CoMeta, we used the exact method for read classification using short subsequences (k-mers) and fast program for indexing large set of k-mers. In contrast to the most popular methods based on BLAST, where the query is compared with each reference sequence, we begin the classification from the top of the taxonomy tree to reduce the number of comparisons. The presented experimental study confirms that CoMeta outperforms other programs used in this context. CoMeta is available at https://github.com/jkawulok/cometa under a free GNU GPL 2 license. </div>
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CoMeta: classification of metagenomes using k-mers.

CoMeta: classification of metagenomes using k-mers.

Source :

English descriptors

Abstract

Links to Exploration step

Le document en format XML

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