Read indexing

Nicolas Philippe (1) , Mikael Salson (2) , Thérèse Commes (3) , Thierry Lecroq (4) , Martine Léonard (4) , Eric Rivals (1)

1 MAB - Méthodes et Algorithmes pour la Bioinformatique
2 BONSAI - Bioinformatics and Sequence Analysis
3 CRBM - Centre de recherche en Biologie Cellulaire
4 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes

The question of read indexing remains broadly unexplored. However, the increase in sequence throughput urges for new algorithmic solutions to query large read collections efficiently. We pro- pose a solution, named Gk arrays, to index large collections of reads, an algorithm to build the structure, and procedures to query it. Once constructed, the index structure is kept in main memory and is repeatedly accessed to answer various types of queries. We compare our data structure to other possible solutions to investigate its scalability and computational efficiency. Gk arrays are im- plemented in a general purpose library, which may prove useful for assembly purposes, for evaluating the expression level in RNA-seq, and others high throughput sequencing applications.

Mots clés: Next Generation Sequencing; stringology; data structure; k-mer; text indexing; scalability; genome; transcriptome; bioinformatics

Domaines: Bio-informatique [q-bio.QM]; Bio-Informatique, Biologie Systémique [q-bio.QM]

Nicolas Philippe, Mikael Salson, Thérèse Commes, Thierry Lecroq, Martine Léonard, et al.. Read indexing. EMBnet.journal, 2011, 17 (Supplement B), pp.1. ⟨10.14806/ej.17.B.289⟩. ⟨lirmm-00757983⟩