DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework
Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method for the identification of genetic variants and has b...
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doaj-c3da8d6dd0dc433c946eaeb37df4364d2020-11-25T03:52:09ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182020-01-01202010.1155/2020/72312057231205DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing FrameworkPo-Jung Huang0Jui-Huan Chang1Hou-Hsien Lin2Yu-Xuan Li3Chi-Ching Lee4Chung-Tsai Su5Yun-Lung Li6Ming-Tai Chang7Sid Weng8Wei-Hung Cheng9Cheng-Hsun Chiu10Petrus Tang11Department of Biomedical Sciences, Chang Gung University, Taoyuan, TaiwanGraduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, TaiwanInstitute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, TaiwanGraduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, TaiwanDepartment of Computer Science and Information Engineering, Chang Gung University, Taoyuan, TaiwanDepartment of Biomedical Sciences, Chang Gung University, Taoyuan, TaiwanDepartment of Biomedical Sciences, Chang Gung University, Taoyuan, TaiwanDepartment of Biomedical Sciences, Chang Gung University, Taoyuan, TaiwanDepartment of Biomedical Sciences, Chang Gung University, Taoyuan, TaiwanDepartment of Parasitology, College of Medicine, Chang Gung University, Taoyuan, TaiwanGenomic Medicine Core Laboratory, Chang Gung Memorial Hospital, Linkou, TaiwanGraduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, TaiwanAlthough sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method for the identification of genetic variants and has been widely used in genome projects and population genetic studies for many years. This was until the Google Brain team developed a new method, DeepVariant, which utilizes deep neural networks to construct an image classification model to identify genetic variants. However, the superior accuracy of DeepVariant comes at the cost of computational intensity, largely constraining its applications. Accordingly, we present DeepVariant-on-Spark to optimize resource allocation, enable multi-GPU support, and accelerate the processing of the DeepVariant pipeline. To make DeepVariant-on-Spark more accessible to everyone, we have deployed the DeepVariant-on-Spark to the Google Cloud Platform (GCP). Users can deploy DeepVariant-on-Spark on the GCP following our instruction within 20 minutes and start to analyze at least ten whole-genome sequencing datasets using free credits provided by the GCP. DeepVaraint-on-Spark is freely available for small-scale genome analysis using a cloud-based computing framework, which is suitable for pilot testing or preliminary study, while reserving the flexibility and scalability for large-scale sequencing projects.http://dx.doi.org/10.1155/2020/7231205 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Po-Jung Huang Jui-Huan Chang Hou-Hsien Lin Yu-Xuan Li Chi-Ching Lee Chung-Tsai Su Yun-Lung Li Ming-Tai Chang Sid Weng Wei-Hung Cheng Cheng-Hsun Chiu Petrus Tang |
spellingShingle |
Po-Jung Huang Jui-Huan Chang Hou-Hsien Lin Yu-Xuan Li Chi-Ching Lee Chung-Tsai Su Yun-Lung Li Ming-Tai Chang Sid Weng Wei-Hung Cheng Cheng-Hsun Chiu Petrus Tang DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework Computational and Mathematical Methods in Medicine |
author_facet |
Po-Jung Huang Jui-Huan Chang Hou-Hsien Lin Yu-Xuan Li Chi-Ching Lee Chung-Tsai Su Yun-Lung Li Ming-Tai Chang Sid Weng Wei-Hung Cheng Cheng-Hsun Chiu Petrus Tang |
author_sort |
Po-Jung Huang |
title |
DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework |
title_short |
DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework |
title_full |
DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework |
title_fullStr |
DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework |
title_full_unstemmed |
DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework |
title_sort |
deepvariant-on-spark: small-scale genome analysis using a cloud-based computing framework |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2020-01-01 |
description |
Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method for the identification of genetic variants and has been widely used in genome projects and population genetic studies for many years. This was until the Google Brain team developed a new method, DeepVariant, which utilizes deep neural networks to construct an image classification model to identify genetic variants. However, the superior accuracy of DeepVariant comes at the cost of computational intensity, largely constraining its applications. Accordingly, we present DeepVariant-on-Spark to optimize resource allocation, enable multi-GPU support, and accelerate the processing of the DeepVariant pipeline. To make DeepVariant-on-Spark more accessible to everyone, we have deployed the DeepVariant-on-Spark to the Google Cloud Platform (GCP). Users can deploy DeepVariant-on-Spark on the GCP following our instruction within 20 minutes and start to analyze at least ten whole-genome sequencing datasets using free credits provided by the GCP. DeepVaraint-on-Spark is freely available for small-scale genome analysis using a cloud-based computing framework, which is suitable for pilot testing or preliminary study, while reserving the flexibility and scalability for large-scale sequencing projects. |
url |
http://dx.doi.org/10.1155/2020/7231205 |
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