Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies. (11th September 2013)

• Record Type: Journal Article
• Authors: Zhao, Shanrong; Prenger, Kurt; Smith, Lance
• Other Names: Lemke N. Academic Editor.; Mizuguchi K. Academic Editor.; Norberto de Souza O. Academic Editor.; Wang J. T. L. Academic Editor.
• Is Part Of: ISRN bioinformatics. Volume 2013(2013)
• Publication Date: 2013-09-11
• Subjects: Bioinformatics -- Periodicals; Computational biology -- Periodicals; Medical informatics -- Periodicals; Computational Biology; Medical Informatics; Bioinformatics; Computational biology; Medical informatics; Periodicals; Periodicals; 570.285
• DOI: 10.1155/2013/481545
• Languages: English
• ISSNs: 2090-7338

Abstract

Abstract : RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets.