Compareads: comparing huge metagenomic experiments

Nicolas Maillet 1, * Claire Lemaitre 1 Rayan Chikhi 1 Dominique Lavenier 1 Pierre Peterlongo 1
* Corresponding author
1 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE, Inria Rennes – Bretagne Atlantique
Abstract : Nowadays, metagenomic sample analyses are mainly achieved by comparing them with a priori knowledge stored in data banks. Even if powerful, such approaches do not allow to exploit unknown and/or "unculturable" species, for instance estimated at 99% for Bacteria. This work introduces Compareads, a de novo comparative metagenomic approach that returns the reads that are similar between two possibly metagenomic datasets generated by High Throughput Sequencers. One originality of this work consists in its ability to deal with huge datasets. The time and memory features make Compareads usable on read sets each composed of more than 100 million Illumina reads in a few hours and consuming 4Gb of memory, and thus usable on today's personal computers. Compareads is released under the CeCILL license and can be freely downloaded from http://alcovna.genouest.org/compareads/.
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https://hal.inria.fr/hal-00760332
Contributor : Nicolas Maillet <>
Submitted on : Monday, December 3, 2012 - 4:56:35 PM
Last modification on : Thursday, February 7, 2019 - 2:43:41 PM
Long-term archiving on : Monday, March 4, 2013 - 3:51:16 AM

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Nicolas Maillet, Claire Lemaitre, Rayan Chikhi, Dominique Lavenier, Pierre Peterlongo. Compareads: comparing huge metagenomic experiments. 13e édition des Journées Ouvertes en Biologie, Informatique et Mathématiques - JOBIM 2012, Jul 2012, Rennes, France. 2012. ⟨hal-00760332⟩

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