MeDuSa: A multi-draft based scaffolder.

Abstract : Completing the genome sequence of an organism is an important task in comparative, functional and structural genomics. However, this remains a challenging issue from both a computational and an experimental viewpoint. Genome scaffolding (i.e. the process of ordering and orientating contigs) of de novo assemblies usually represents the first step in most genome finishing pipelines. In this paper, we present MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalises the scaffolding problem by means of a combinatorial optimisation formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries. This makes usability and running time two additional important features of our method. Moreover, benchmarks and tests on real bacterial datasets showed that MeDuSa is highly accurate and, in most cases, outperforms traditional scaffolders. The possibility to use MeDuSa on eukaryotic datasets has also been evaluated, leading to interesting results. MeDuSa web server: http://combo.dbe.unifi.it/medusa A stand-alone version of the software can be downloaded from https://github.com/combogenomics/medusa/releases. All results presented in this work have been obtained with MeDuSa v. 1.3. marco.fondi@unifi.it.
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https://hal.inria.fr/hal-01139506
Contributeur : Marie-France Sagot <>
Soumis le : lundi 6 avril 2015 - 08:44:46
Dernière modification le : jeudi 19 avril 2018 - 14:49:48

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Emanuele Bosi, Beatrice Donati, Marco Galardini, Sara Brunetti, Marie-France Sagot, et al.. MeDuSa: A multi-draft based scaffolder.. Bioinformatics (Oxford, England), 2015, pii: btv171 [Epub ahead of print]. 〈10.1093/bioinformatics/btv171〉. 〈hal-01139506〉

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