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

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 far from...

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Dades bibliogràfiques
Publicat a:BMC Genomics
Autors principals: Wang, Yiqi, Li, Gen, Ma, Mark, He, Fazhong, Song, Zhuo, Zhang, Wei, Wu, Chengkun
Format: Artigo
Idioma:Inglês
Publicat: BioMed Central 2018
Matèries:
Research
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC5780748/
https://ncbi.nlm.nih.gov/pubmed/29363427
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12864-017-4334-x
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