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CoMeta: Classification of Metagenomes Using k-mers

Identifieur interne : 001860 ( Main/Exploration ); précédent : 001859; suivant : 001861

CoMeta: Classification of Metagenomes Using k-mers

Auteurs : Jolanta Kawulok ; Sebastian Deorowicz

Source :

RBID : PMC:4401624

Descripteurs français

English descriptors

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.


Url:
DOI: 10.1371/journal.pone.0121453
PubMed: 25884504
PubMed Central: 4401624


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<p>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 (
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