title: CRAC: an integrated approach to the analysis of RNA-seq reads.
abstract: A large number of RNA-sequencing studies set out to predict mutations, splice junctions or fusion RNAs. We propose a method, CRAC, that integrates genomic locations and local coverage to enable such predictions to be made directly from RNA-seq read analysis. A k-mer profiling approach detects candidate mutations, indels and splice or chimeric junctions in each single read. CRAC increases precision compared with existing tools, reaching 99:5% for splice junctions, without losing sensitivity. Importantly, CRAC predictions improve with read length. In cancer libraries, CRAC recovered 74% of validated fusion RNAs and predicted novel recurrent chimeric junctions. CRAC is available at http://crac.gforge.inria.fr.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Philippe
authors.forename: Mikaël
authors.initials: M
authors.lastname: Salson
authors.forename: Thérèse
authors.initials: T
authors.lastname: Commes
authors.forename: Eric
authors.initials: E
authors.lastname: Rivals
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics; D003198:Computer Simulation; D005260:Female; D015723:Gene Library; D016678:Genome; D006801:Humans; D022821:RNA Splice Sites / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods*
chemical_list: D022821:RNA Splice Sites
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