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

Research output: Contribution to journalArticlepeer-review

94 Scopus citations

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/.

Original languageEnglish (US)
Pages (from-to)2224-2226
Number of pages3
JournalBioinformatics
Volume30
Issue number15
DOIs
StatePublished - Aug 1 2014
Externally publishedYes

ASJC Scopus subject areas

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

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