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PRADA: pipeline for RNA sequencing data analysis.
Torres-García, Wandaliz; Zheng, Siyuan; Sivachenko, Andrey; Vegesna, Rahulsimham; Wang, Qianghu; Yao, Rong; Berger, Michael F; Weinstein, John N; Getz, Gad; Verhaak, Roel G W.
Afiliação
  • Torres-García W; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Zheng S; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Sivachenko A; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Vegesna R; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Wang Q; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Yao R; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Berger MF; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Weinstein JN; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Getz G; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
  • Verhaak RG; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, The Eli and Edythe L. Broad Institute of Harvard University and MIT, Cambridge, MA 02142 and Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY 100
Bioinformatics ; 30(15): 2224-6, 2014 Aug 01.
Article em En | MEDLINE | ID: mdl-24695405
ABSTRACT

SUMMARY:

Technological advances in high-throughput sequencing necessitate improved computational tools for processing and analyzing large-scale datasets in a systematic automated manner. For that purpose, we have developed PRADA (Pipeline for RNA-Sequencing Data Analysis), a flexible, modular and highly scalable software platform that provides many different types of information available by multifaceted analysis starting from raw paired-end RNA-seq data gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification. PRADA uses a dual-mapping strategy that increases sensitivity and refines the analytical endpoints. PRADA has been used extensively and successfully in the glioblastoma and renal clear cell projects of The Cancer Genome Atlas program. AVAILABILITY AND IMPLEMENTATION http//sourceforge.net/projects/prada/ CONTACT gadgetz@broadinstitute.org or rverhaak@mdanderson.org SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Estatística como Assunto / Análise de Sequência de RNA Idioma: En Ano de publicação: 2014 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Estatística como Assunto / Análise de Sequência de RNA Idioma: En Ano de publicação: 2014 Tipo de documento: Article