{"title":"Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies.","authors":"Shanrong Zhao, Kurt Prenger, Lance Smith","doi":"10.1155/2013/481545","DOIUrl":null,"url":null,"abstract":"<p><p>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. </p>","PeriodicalId":90877,"journal":{"name":"ISRN bioinformatics","volume":"2013 ","pages":"481545"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2013/481545","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISRN bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2013/481545","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2013/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
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.
RNA-Seq正在成为转录组分析和差异基因表达研究中微阵列的有希望的替代品。技术的进步降低了测序成本,因此,RNA-Seq数据集的大小和数量迅速增加。然而,大规模RNA-Seq研究的数据量不断增加,对局部环境下的数据分析提出了实际挑战。为了应对这一挑战,我们开发了基于云的软件包Stormbow,以并行处理大量RNA-Seq数据。Stormbow的性能已经通过实际应用它来分析云中178个RNA-Seq样本进行了测试。在我们的测试中,处理1亿个reads的RNA-Seq样本需要6到8个小时,每个样本的平均成本为3.5美元。利用Amazon Web Services作为Stormbow的基础设施,我们可以通过按需计算资源轻松扩展以处理大型数据集。Stormbow是一个可扩展的、成本有效的、基于开源的大规模RNA-Seq数据分析工具。Stormbow可以免费下载,并且可以开箱即用来处理Illumina RNA-Seq数据集。