GT-WGS: an efficient and economic tool for large-scale WGS analyses based on the AWS cloud service

GT-WGS: an efficient and economic tool for large-scale WGS analyses based on the AWS cloud service

Abstract Background Whole-genome sequencing (WGS) plays an increasingly important role in clinical practice and public health. Due to the big data size, WGS data analysis is usually compute-intensive and IO-intensive. Currently it usually takes 30 to 40 h to finish a 50× WGS analysis task, which is...

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Bibliographic Details
Main Authors: Yiqi Wang, Gen Li, Mark Ma, Fazhong He, Zhuo Song, Wei Zhang, Chengkun Wu
Format: Article
Language:English
Published: BMC 2018-01-01
Series:BMC Genomics
Subjects:
Whole-genome sequencing
AWS
Parallel and distributed computing
Online Access:http://link.springer.com/article/10.1186/s12864-017-4334-x

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http://link.springer.com/article/10.1186/s12864-017-4334-x

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