Related Experiment Video
Updated: Jan 19, 2026
Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
Published on: May 9, 2017
SimkaMin: fast and resource frugal de novo comparative metagenomics
Gaëtan Benoit1, Mahendra Mariadassou2, Stéphane Robin3
1Univ Rennes, Inria, CNRS, IRISA, F-35000 Rennes, France.
Motivation:
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.
Results:
We present SimkaMin, a quick comparative metagenomics tool with low disk and memory footprints, thanks to an efficient data subsampling scheme used to estimate Bray-Curtis and Jaccard dissimilarities. One billion metagenomic reads can be analyzed in <3 min, with tiny memory (1.09 GB) and disk (≈0.3 GB) requirements and without altering the quality of the downstream comparative analyses, making of SimkaMin a tool perfectly tailored for very large-scale metagenomic projects.
Availability And Implementation:
https://github.com/GATB/simka.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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