Spaced seeds improve k-mer-based metagenomic classification - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue Bioinformatics Année : 2015

Spaced seeds improve k-mer-based metagenomic classification

Résumé

Motivation: Metagenomics is a powerful approach to study genetic content of environmental samples, which has been strongly promoted by next-generation sequencing technologies. To cope with massive data involved in modern metagenomic projects, recent tools rely on the analysis of k-mers shared between the read to be classified and sampled reference genomes. Results: Within this general framework, we show that spaced seeds provide a significant improvement of classification accuracy, as opposed to traditional contiguous k-mers. We support this thesis through a series of different computational experiments, including simulations of large-scale metagenomic projects. Availability and implementation, Supplementary information: Scripts and programs used in this study, as well as supplementary material, are available from http://github.com/gregorykucherov/spaced-seeds-for-metagenomics.

Dates et versions

hal-01250752 , version 1 (05-01-2016)

Identifiants

Citer

Karel Brinda, Maciej Sykulski, Gregory Kucherov. Spaced seeds improve k-mer-based metagenomic classification. Bioinformatics, 2015, ⟨10.1093/bioinformatics/btv419⟩. ⟨hal-01250752⟩
94 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More