An Open-source Azure Solution for Scalable Genomics Workflows

被引：1

作者：

Yang-Turner, Fan ^{[1
]}

Gripper, Lawrence ^{[2
]}

Swann, Jeremy ^{[1
]}

Do, Trien ^{[1
]}

Foster, Dona ^{[1
]}

Volk, Denis ^{[1
]}

Ramanan, Anita ^{[2
]}

Robinson, Marcus ^{[2
]}

Peto, Tim ^{[1
]}

Crook, Derrick ^{[1
]}

机构：

[1] Univ Oxford, Nuffield Dept Clin Med, Oxford, England

[2] Microsoft CSE, London, England

来源：

2018 IEEE WORLD CONGRESS ON SERVICES (IEEE SERVICES 2018) | 2018年

关键词：

scientific workflow; container; cluster system; genomic data analytics; bioinformatic pipeline; cloud computing;

D O I：

10.1109/SERVICES.2018.00033

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present an open-source Azure solution for running scalable genomics workflows. It benefits from state-of-art distributed workflow framework, container and cloud technologies and allows users to create a cluster that is scaled to suit their workload in minutes. We describe the design decisions, solution testing and automation options to support a variety of users for their genomic data analytics. The solution demonstrates a generic and customizable approach to run genomic data analytics workflows on a cloud environment

引用

页码：39 / 40

页数：2

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