Spaced seeds improve k-mer-based metagenomic classification


Břinda, K., Sykulski, M., & Kucherov, G. (2015). Spaced seeds improve k-mer-based metagenomic classification. Bioinformatics , 31 (22), 3584–3592. Copy at

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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

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Last updated on 12/09/2018