Tracking the NGS revolution: managing life science research on shared high-performance computing clusters | Zendy

Martin Dahlö | Zendy; Douglas G. Scofield | Zendy; Wesley Schaal | Zendy; Ola Spjuth | Zendy

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Tracking the NGS revolution: managing life science research on shared high-performance computing clusters

Author(s) -

Martin Dahlö,

Douglas G. Scofield,

Wesley Schaal,

Ola Spjuth

Publication year - 2018

Publication title -

gigascience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.947

H-Index - 54

ISSN - 2047-217X

DOI - 10.1093/gigascience/giy028

Subject(s) - computer science , data science , set (abstract data type) , database , programming language

Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences.

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