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A de novo approach to disentangle partner identity and function in holobiont systems

Authors
  • Meng, Arnaud
  • Marchet, Camille
  • Corre, Erwan
  • Peterlongo, Pierre
  • Alberti, Adriana
  • Da Silva, Corinne
  • Wincker, Patrick
  • Pelletier, Eric
  • Probert, Ian
  • Decelle, Johan
  • Le Crom, Stéphane
  • Not, Fabrice
  • Bittner, Lucie
Publication Date
Nov 21, 2017
Source
Kaleidoscope Open Archive
Keywords
Language
English
License
Unknown
External links

Abstract

This work addresses the problem of grouping by genes long reads expressed in a wholetranscriptome sequencing data set. Long read sequencing produces several thousands base-pair long sequences, although showing high error rate in comparison to short reads. Longreads can cover full-length RNA transcripts and thus are of high interest to complete refer-ences. However, the literature is lacking tools to cluster such data de novo, in particular forOxford Nanopore Technologies reads. As a consequence, we propose a novel algorithm basedon community detection and its implementation. Since solution is meant to be reference-free(de novo), it is especially well-tailored for non model species. We demonstrate it performswell on a real mouse data set. When a reference is available, we show that it stands as analternative to mapping. In addition, we show that quick assessment of gene's expression isa straightforward use case of our solution.

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