Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript (Articolo in rivista)

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  • Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript (Articolo in rivista) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Alternative label
  • Benelli M(a,b), Pescucci C(b ), Marseglia G(b), Severgnini M (c), Torricelli F (a,b), Magi A (b,d) (2012)
    Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript
    in Bioinformatics (Oxf., Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Benelli M(a,b), Pescucci C(b ), Marseglia G(b), Severgnini M (c), Torricelli F (a,b), Magi A (b,d) (literal)
Pagina inizio
  • 3232 (literal)
Pagina fine
  • 3239 (literal)
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  • cited By (since 1996)2 (literal)
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  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84870815979&partnerID=40&md5=650f1f4d4cdd93f252b274741dca95bf (literal)
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  • 28 (literal)
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  • 24 (literal)
Note
  • Scopu (literal)
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  • a Diagnostic Genetic Unit, Laboratory Department, Careggi University Hospital, 50134 Florence, Italy; b Center for the Study of Complex Dynamics, University of Florence, 50019 Florence, Italy; c Institute of Biomedical Technologies (ITB), National Research Council (CNR), 20090 Segrate, Italy; d Department of Medical and Surgical Critical Care, University of Florence, 50134 Florence, Italy (literal)
Titolo
  • Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript (literal)
Abstract
  • Motivation: The discovery of novel gene fusions can lead to a better comprehension of cancer progression and development. The emergence of deep sequencing of trancriptome, known as RNA-seq, has opened many opportunities for the identification of this class of genomic alterations, leading to the discovery of novel chimeric transcripts in melanomas, breast cancers and lymphomas. Nowadays, few computational approaches have been developed for the detection of chimeric transcripts. Although all of these computational methods show good sensitivity, much work remains to reduce the huge number of false-positive calls that arises from this analysis.Results: We proposed a novel computational framework, named chimEric tranScript detection algorithm (EricScript), for the identification of gene fusion products in paired-end RNA-seq data. Our simulation study on synthetic data demonstrates that EricScript enables to achieve higher sensitivity and specificity than existing methods with noticeably lower running times. We also applied our method to publicly available RNA-seq tumour datasets, and we showed its capability in rediscovering known gene fusions.Availability: The EricScript package is freely available under GPL v3 license at http://ericscript.sourceforge.net. © 2012 The Author. (literal)
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