Novel approaches for the exploitation of high throughput sequencing data

Antoine Limasset 1
1 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
Inria Rennes – Bretagne Atlantique , IRISA_D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : In this thesis we discuss computational methods to deal with DNA sequences provided by high throughput sequencers. We will mostly focus on the reconstruction of genomes from DNA fragments (genome assembly) and closely related problems. These tasks combine huge amounts of data with combinatorial problems. Various graph structures are used to handle this problem, presenting trade-off between scalability and assembly quality. This thesis introduces several contributions in order to cope with these tasks. First, novel representations of assembly graphs are proposed to allow a better scaling. We also present novel uses of those graphs apart from assembly and we propose tools to use such graphs as references when a fully assembled genome is not available. Finally we show how to use those methods to produce less fragmented assembly while remaining tractable.
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Submitted on : Friday, July 21, 2017 - 2:28:15 PM
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  • HAL Id : tel-01566938, version 1

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Antoine Limasset. Novel approaches for the exploitation of high throughput sequencing data. Bioinformatics [q-bio.QM]. Université Rennes 1, 2017. English. ⟨tel-01566938⟩

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