SimkaMin: fast and resource frugal de novo comparative metagenomics | Zendy

Gaëtan Benoit | Zendy; Mahendra Mariadassou | Zendy; Stéphane Robin | Zendy; Sophie Schbath | Zendy; Pierre Peterlongo | Zendy; Claire Lemaitre | Zendy

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SimkaMin: fast and resource frugal de novo comparative metagenomics

Author(s) -

Gaëtan Benoit,

Mahendra Mariadassou,

Stéphane Robin,

Sophie Schbath,

Pierre Peterlongo,

Claire Lemaitre

Publication year - 2019

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btz685

Subject(s) - metagenomics , jaccard index , computer science , computational biology , data mining , similarity (geometry) , resource (disambiguation) , biology , cluster analysis , artificial intelligence , genetics , gene , computer network , image (mathematics)

De novo comparative metagenomics is one of the most straightforward ways to analyze large sets of metagenomic data. Latest methods use the fraction of shared k-mers to estimate genomic similarity between read sets. However, those methods, while extremely efficient, are still limited by computational needs for practical usage outside of large computing facilities.

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