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Improved transcriptome quantification and reconstruction from RNA-Seq reads using partial annotations.
Mangul, Serghei; Caciula, Adrian; Glebova, Olga; Mandoiu, Ion; Zelikovsky, Alex.
Afiliação
  • Mangul S; Department of Computer Science, Georgia State University, Atlanta, GA, USA. serghei@cs.gsu.edu
In Silico Biol ; 11(5-6): 251-61, 2011.
Article em En | MEDLINE | ID: mdl-23202426
ABSTRACT
The paper addresses the problem of how to use RNA-Seq data for transcriptome reconstruction and quantification, as well as novel transcript discovery in partially annotated genomes. We present a novel annotation-guided general framework for transcriptome discovery, reconstruction and quantification in partially annotated genomes and compare it with existing annotation-guided and genome-guided transcriptome assembly methods. Our method, referred as Discovery and Reconstruction of Unannotated Transcripts (DRUT), can be used to enhance existing transcriptome assemblers, such as Cufflinks, as well as to accurately estimate the transcript frequencies. Empirical analysis on synthetic datasets confirms that Cufflinks enhanced by DRUT has superior quality of reconstruction and frequency estimation of transcripts.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sequenciamento de Nucleotídeos em Larga Escala / Transcriptoma Limite: Humans Idioma: En Ano de publicação: 2011 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sequenciamento de Nucleotídeos em Larga Escala / Transcriptoma Limite: Humans Idioma: En Ano de publicação: 2011 Tipo de documento: Article