A de novo approach to disentangle partner identity and function in holobiont systems
Résumé
This work addresses the problem of grouping by genes long reads expressed in a whole
transcriptome sequencing data set. Long read sequencing produces several thousands base-
pair long sequences, although showing high error rate in comparison to short reads. Long
reads 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 for
Oxford Nanopore Technologies reads. As a consequence, we propose a novel algorithm based
on 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 performs
well on a real mouse data set. When a reference is available, we show that it stands as an
alternative to mapping. In addition, we show that quick assessment of gene's expression is
a straightforward use case of our solution.
| Origine | Fichiers produits par l'(les) auteur(s) |
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