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CRAC: an integrated approach to the analysis of RNA-seq reads

Nicolas Philippe125, Mikaël Salson34, Thérèse Commes25 and Eric Rivals15*

  • * Corresponding author: Eric Rivals rivals@lirmm.fr

  • † Equal contributors

Author Affiliations

1 Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), UMR 5506, CNRS and Université de Montpellier 2, 161 rue Ada, 34095 Montpellier Cedex 5, France

2 Institut de Recherche en Biothérapie (IRB), U1040 INSERM, CHRU Montpellier Hôpital Saint-Eloi 80, av. Augustin Fliche, 34295 Montpellier Cedex 5, France

3 Laboratoire d'Informatique Fondamentale de Lille (LIFL), (UMR CNRS 8022, Université Lille 1) and Inria Lille-Nord Europe, Cité scientifique-Bâtiment M3, 59655 Villeneuve d'Ascq Cedex, France

4 LITIS EA 4108, Université de Rouen, 1 rue Thomas Becket, 76821 Mont-Saint-Aignan Cedex, France

5 Institut de Biologie Computationnelle, 95 Rue de la Galéra, 34095 Montpellier Cedex 5, France

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Genome Biology 2013, 14:R30  doi:10.1186/gb-2013-14-3-r30

Published: 28 March 2013

Additional files

Additional file 1:

Figure with read classification performed by CRAC.

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Open Data

Additional file 2:

Additional description of the CRAC algorithm, the simulation of RNA-seq data, and the tools used for comparison.

Format: PDF Size: 487KB Download file

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Additional file 3:

Results for simulated RNA-seq data.

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Additional file 4:

Results for real RNA-seq data.

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Open Data

Additional file 5:

Table with chimeric RNAs predicted for four breast cancer libraries.

Format: ODS Size: 328KB Download file

Open Data