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

  • 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
Kaleidoscope Open Archive
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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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