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RASflow: an RNA-Seq analysis workflow with Snakemake.
BMC Bioinformatics ( IF 2.9 ) Pub Date : 2020-03-18 , DOI: 10.1186/s12859-020-3433-x
Xiaokang Zhang 1 , Inge Jonassen 1
Affiliation  

With the cost of DNA sequencing decreasing, increasing amounts of RNA-Seq data are being generated giving novel insight into gene expression and regulation. Prior to analysis of gene expression, the RNA-Seq data has to be processed through a number of steps resulting in a quantification of expression of each gene/transcript in each of the analyzed samples. A number of workflows are available to help researchers perform these steps on their own data, or on public data to take advantage of novel software or reference data in data re-analysis. However, many of the existing workflows are limited to specific types of studies. We therefore aimed to develop a maximally general workflow, applicable to a wide range of data and analysis approaches and at the same time support research on both model and non-model organisms. Furthermore, we aimed to make the workflow usable also for users with limited programming skills. Utilizing the workflow management system Snakemake and the package management system Conda, we have developed a modular, flexible and user-friendly RNA-Seq analysis workflow: RNA-Seq Analysis Snakemake Workflow (RASflow). Utilizing Snakemake and Conda alleviates challenges with library dependencies and version conflicts and also supports reproducibility. To be applicable for a wide variety of applications, RASflow supports the mapping of reads to both genomic and transcriptomic assemblies. RASflow has a broad range of potential users: it can be applied by researchers interested in any organism and since it requires no programming skills, it can be used by researchers with different backgrounds. The source code of RASflow is available on GitHub: https://github.com/zhxiaokang/RASflow. RASflow is a simple and reliable RNA-Seq analysis workflow covering many use cases.

中文翻译:

RASflow:带有Snakemake的RNA-Seq分析工作流程。

随着DNA测序成本的降低,越来越多的RNA-Seq数据正在产生,从而为基因表达和调控提供了新颖的见解。在分析基因表达之前,必须通过多个步骤处理RNA-Seq数据,以量化每个分析样品中每个基因/转录物的表达。有许多工作流程可帮助研究人员对自己的数据或对公共数据执行这些步骤,以在数据重新分析中利用新颖的软件或参考数据。但是,许多现有的工作流程仅限于特定类型的研究。因此,我们旨在开发一种最大程度的通用工作流程,以适用于各种数据和分析方法,同时支持对模型生物和非模型生物的研究。此外,我们旨在使工作流程也可用于编程技能有限的用户。利用工作流管理系统Snakemake和程序包管理系统Conda,我们开发了一种模块化,灵活且用户友好的RNA-Seq分析工作流:RNA-Seq分析Snakemake工作流(RASflow)。利用Snakemake和Conda可以减轻库依赖性和版本冲突带来的挑战,并且还支持可重现性。为了适用于各种各样的应用程序,RASflow支持将读取映射到基因组和转录组。RASflow具有广泛的潜在用户:可以由对任何生物感兴趣的研究人员使用,并且它不需要编程技能,因此可以由具有不同背景的研究人员使用。RASflow的源代码可在GitHub上找到:https:// github。com / zhxiaokang / RASflow。RASflow是一种简单可靠的RNA-Seq分析工作流程,涉及许多用例。
更新日期:2020-04-22
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