CWL-Airflow: a lightweight pipeline manager supporting Common Workflow Language
CWL-Airflow: a lightweight pipeline manager supporting Common Workflow Language
复制标题
CWL-Airflow：支持通用工作流语言的轻量级管道管理器
作者：
M. Kotliar;A. Kartashov;A. Barski
研究数据和计算分析量的大量增长导致生物医学计算研究中管道管理器的利用率增加。然而，在100多个这样的管理器中，每一个都使用自己的方式来描述管道，导致难以将工作流移植到不同的环境中，因此计算研究的可重复性很差。由于这个原因，最近引入了通用工作流语言（CWL）作为独立于平台的工作流描述规范，并且开始将现有的管道和工作流管理器转换为CWL。在这里，我们提出了CWL-Airflow，这是支持CWL的Apache气流管道管理器的扩展。CWL- airflow使用CWL v1.0规范，可用于在独立的MacOS/Linux服务器、集群或各种云平台上运行工作流。给出了一个用于处理ChIP-Seq数据的示例CWL管道。CWL-Airflow将为用户提供一个成熟的管道管理器的功能，并能够在任何地方执行CWL工作流，从笔记本电脑到集群或云环境。可用性CWL-Airflow在Apache v.2许可下可用，可以从https://barski-lab.github.io/cwl-airflow、http://doi.org/10.5281/zenodo.2669582、RRID: SCR_017196下载。
Background Massive growth in the amount of research data and computational analysis has led to increased utilization of pipeline managers in biomedical computational research. However, each of more than 100 such managers uses its own way to describe pipelines, leading to difficulty porting workflows to different environments and therefore poor reproducibility of computational studies. For this reason, the Common Workflow Language (CWL) was recently introduced as a specification for platform-independent workflow description, and work began to transition existing pipelines and workflow managers to CWL. Findings Here, we present CWL-Airflow, an extension for the Apache Airflow pipeline manager supporting CWL. CWL-Airflow utilizes CWL v1.0 specification and can be used to run workflows on standalone MacOS/Linux servers, on clusters, or on a variety of cloud platforms. A sample CWL pipeline for processing of ChIP-Seq data is provided. Conclusions CWL-Airflow will provide users with the features of a fully-fledged pipeline manager and an ability to execute CWL workflows anywhere Airflow can run—from a laptop to cluster or cloud environment. Availability CWL-Airflow is available under Apache license v.2 and can be downloaded from https://barski-lab.github.io/cwl-airflow, http://doi.org/10.5281/zenodo.2669582, RRID: SCR_017196.
影响因子：
7
作者：
Giardine, B;Riemer, C;Nekrutenko, A
通讯作者：
Nekrutenko, A
使用 BioWardrobe 分析 ChIP-Seq 和 RNA-Seq 数据。
DOI：
10.1007/978-1-4939-7834-2_17
发表时间：
2018
期刊：
Methods in molecular biology (Clifton, N.J.)
影响因子：
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作者：
Vallabh,Sushmitha;Kartashov,AndreyV;Barski,Artem
通讯作者：
Barski,Artem