Comparaison de novo de données de séquençage issues de très grands échantillons métagénomiques : application sur le projet Tara Oceans

Nicolas Maillet 1
1 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : Metagenomics studies overall genomic information of multiple organisms coming from the same biotope. The information is generally provided by next generation sequencing technologies (NGS). Typical data are samples of short reads (i.e. reads of few hundred base pairs). To study such metagenomics information, we developed an original method for extracting similarities between two samples of reads. More precisely, this approach locates the set of common reads present in two samples. In order to fit with current memory capacities and to be time efficient, we used a modified Bloom filter data structure. Finding the common reads between multiple samples and crossing this information with the location of samples leads to visualize some biological processes like ubiquitous species or effect of water stream caring some species. Finally, the tool can also be used as a filter on metagenomics datas to remove for example only one specie. Our software, Compareads, is actually used on the Tara Oceans project where it shows that global dynamic of oceans seems to play a part on the dispersion of marine microorganisms.
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Nicolas Maillet. Comparaison de novo de données de séquençage issues de très grands échantillons métagénomiques : application sur le projet Tara Oceans. Autre [cs.OH]. Université Rennes 1, 2013. Français. ⟨NNT : 2013REN1S097⟩. ⟨tel-00941922⟩

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