PRADA: Pipeline for RNA sequencing data analysis

Wandaliz Torres-García, Siyuan Zheng, Andrey Sivachenko, Rahulsimham Vegesna, Qianghu Wang, Rong Yao, Michael F. Berger, John N. Weinstein, Gad Getz, Roel G.W. Verhaak

Producción científica: Articlerevisión exhaustiva

121 Citas (Scopus)

Resumen

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/.

Idioma originalEnglish (US)
Páginas (desde-hasta)2224-2226
Número de páginas3
PublicaciónBioinformatics
Volumen30
N.º15
DOI
EstadoPublished - ago 1 2014

ASJC Scopus subject areas

  • Computational Mathematics
  • Molecular Biology
  • Biochemistry
  • Statistics and Probability
  • Computer Science Applications
  • Computational Theory and Mathematics

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