KISSPLICE: de-novo calling alternative splicing events from RNA-seq data

Gustavo Sacomoto 1, 2 Janice Kielbassa 1, 2 Rayan Chikhi 3 Raluca Uricaru 1, 3, 4 Pavlos Antoniou 1 Marie-France Sagot 5, 2, * Pierre Peterlongo 3, * Vincent Lacroix 5, 2, *
* Corresponding author
2 BAMBOO - An algorithmic view on genomes, cells, and environments
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
3 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE, Inria Rennes – Bretagne Atlantique
5 Baobab
PEGASE - Département PEGASE [LBBE]
Abstract : In this paper, we address the problem of identifying and quantifying polymorphisms in RNA-seq data when no reference genome is available, without assembling the full transcripts. Based on the fundamental idea that each polymorphism corresponds to a recognisable pattern in a De Bruijn graph constructed from the RNA-seq reads, we propose a general model for all polymorphisms in such graphs. We then introduce an exact algorithm, called KISSPLICE, to extract alternative splicing events. We show that KISSPLICE enables to identify more correct events than general purpose transcriptome assemblers. Additionally, on a 71 M reads dataset from human brain and liver tissues, KISSPLICE identified 3497 alternative splicing events, out of which 56% are not present in the annotations, which confirms recent estimates showing that the complexity of alternative splicing has been largely underestimated so far. We propose new models and algorithms for the detection of polymorphism in RNA-seq data. This opens the way to a new kind of studies on large HTS RNA-seq datasets, where the focus is not the global reconstruction of full-length transcripts, but local assembly of polymorphic regions. KISSPLICE is available for download at http://alcovna.genouest.org/kissplice/.
Liste complète des métadonnées

Cited literature [19 references]  Display  Hide  Download

https://hal.inria.fr/hal-00784407
Contributor : Ed. Bmc <>
Submitted on : Monday, February 4, 2013 - 1:01:21 PM
Last modification on : Thursday, April 18, 2019 - 3:14:58 PM
Document(s) archivé(s) le : Monday, June 17, 2013 - 6:37:36 PM

Files

Identifiers

Citation

Gustavo Sacomoto, Janice Kielbassa, Rayan Chikhi, Raluca Uricaru, Pavlos Antoniou, et al.. KISSPLICE: de-novo calling alternative splicing events from RNA-seq data. BMC Bioinformatics, BioMed Central, 2012, 13 (Suppl 6), pp.S5. ⟨10.1186/1471-2105-13-S6-S5⟩. ⟨hal-00784407⟩

Share

Metrics

Record views

1156

Files downloads

851