CRAC: A multi-purpose program to analyse large read collections

Eric Rivals 1, *
* Auteur correspondant
1 MAB - Méthodes et Algorithmes pour la Bioinformatique
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : The processing of huge collection of sequencing reads obtained with High Throughput Sequencing (HTS) technologies currently demands for their analysis complex processing pipelines and hours or even days of computing. Numerous articles present processing pipelines able to predict for genomic or transcriptomic reads one type of biological events like small mutations, insertions-deletions, rearrangements, or either normal or chimeric splice junctions (in transcriptomic data). We will present, CRAC, a new read analysis program that fulfills multiple purposes in the sense that it can predict simultaneously, in a single analysis step, the different kinds of above-mentioned biological events, including junctions of chimeric RNAs. Thus, CRAC simplifies genomic or transcriptomic read analysis from the user's point of view. It includes sequencing error detection to avoid confusion with true mutations. Moreover, integrating all predictions in a single step improves the sensitivity and specificity of the predictions. We will show that compared to other current solutions CRAC delivers multiple predictions in highly competitive computing times. CRAC constitutes the basis of a HTS analysis service available at the ATGC bioinformatics platform http://www.atgc-montpellier.fr/ngs/.
Type de document :
Communication dans un congrès
Martin Figeac and David Hot and Guillemette Marot and Hélène Touzet. Analyse bio-informatique des données NGS, Dec 2011, Institut Pasteur de Lille, France. 2011, 〈http://www.lifl.fr/bonsai/seqbio2011/ngs11.html〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00832549
Contributeur : Eric Rivals <>
Soumis le : lundi 10 juin 2013 - 22:50:34
Dernière modification le : jeudi 11 janvier 2018 - 06:26:13

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  • HAL Id : lirmm-00832549, version 1

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Eric Rivals. CRAC: A multi-purpose program to analyse large read collections. Martin Figeac and David Hot and Guillemette Marot and Hélène Touzet. Analyse bio-informatique des données NGS, Dec 2011, Institut Pasteur de Lille, France. 2011, 〈http://www.lifl.fr/bonsai/seqbio2011/ngs11.html〉. 〈lirmm-00832549〉

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