Motivation: The discovery of novel gene fusions can lead to a better comprehension of cancer progression and development. The emer- gence of deep sequencing of trancriptome, known as RNA-seq, has opened many opportunities for the identification of this class of gen- omic alterations, leading to the discovery of novel chimeric transcripts in melanomas, breast cancers and lymphomas. Nowadays, few com- putational approaches have been developed for the detection of chi- meric 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 identifica- tion of gene fusion products in paired-end RNA-seq data. Our simu- lation 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 pub- licly 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.

Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript / Benelli M;Pescucci C;Marseglia G;Severgnini M;Torricelli F;Magi A. - In: BIOINFORMATICS. - ISSN 1367-4803. - ELETTRONICO. - (2012), pp. 3232-3239. [10.1093/bioinformatics/bts617]

Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript.

BENELLI, MATTEO;MAGI, ALBERTO
2012

Abstract

Motivation: The discovery of novel gene fusions can lead to a better comprehension of cancer progression and development. The emer- gence of deep sequencing of trancriptome, known as RNA-seq, has opened many opportunities for the identification of this class of gen- omic alterations, leading to the discovery of novel chimeric transcripts in melanomas, breast cancers and lymphomas. Nowadays, few com- putational approaches have been developed for the detection of chi- meric 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 identifica- tion of gene fusion products in paired-end RNA-seq data. Our simu- lation 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 pub- licly 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
3232
3239
Benelli M;Pescucci C;Marseglia G;Severgnini M;Torricelli F;Magi A
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/780310
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