Cloud computing for genomic data analysis and collaboration

Ben Langmead, Abhinav Nellore

Research output: Contribution to journalReview article

31 Citations (Scopus)

Abstract

Next-generation sequencing has made major strides in the past decade. Studies based on large sequencing data sets are growing in number, and public archives for raw sequencing data have been doubling in size every 18 months. Leveraging these data requires researchers to use large-scale computational resources. Cloud computing, a model whereby users rent computers and storage from large data centres, is a solution that is gaining traction in genomics research. Here, we describe how cloud computing is used in genomics for research and large-scale collaborations, and argue that its elasticity, reproducibility and privacy features make it ideally suited for the large-scale reanalysis of publicly available archived data, including privacy-protected data.

Original languageEnglish (US)
Pages (from-to)208-219
Number of pages12
JournalNature Reviews Genetics
Volume19
Issue number4
DOIs
StatePublished - Apr 1 2018

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Privacy
Genomics
Information Storage and Retrieval
Elasticity
Traction
Research
Research Personnel
Cloud Computing
Datasets

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)

Cite this

Cloud computing for genomic data analysis and collaboration. / Langmead, Ben; Nellore, Abhinav.

In: Nature Reviews Genetics, Vol. 19, No. 4, 01.04.2018, p. 208-219.

Research output: Contribution to journalReview article

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