Genomics and big data in biomedicine

Authored by: Niccolò Tempini , Sabina Leonelli

Handbook of Genomics, Health and Society

Print publication date:  April  2018
Online publication date:  April  2018

Print ISBN: 9781138211957
eBook ISBN: 9781315451695
Adobe ISBN:

10.4324/9781315451695-4

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Abstract

The ease with which genomic data can be generated and disseminated, and particularly the novel opportunities offered by the fast and cheap genotyping of individual patients, is resulting in the building of large-scale online databases. These include infrastructures supporting the exchange, integration and interpretation of health-related data as well as tools designed to facilitate the analysis of clinical situations (Merelli et al., 2014; Staes et al., 2009; Wang & Krishnan, 2014). These databases collate and provide access to data produced at high velocity, thanks to increasing levels of automation and standardisation in the sequencing pipeline; in great volume, since a single genome off the sequencer can require up to 180 gigabytes of disk space; and coming from a vast variety of sources, both in the institutional and geographical sense of encompassing many different locations of data production and the epistemic sense of including many types of high-throughput biomedical data beyond the genome, such as transcriptomics, proteomics, metabolomics and so on. Thus exemplifying the 3Vs definition often used to characterise Big Data (Kitchin, 2013), genomics is widely regarded as a prominent example of how Big Data collection and analysis can result in novel approaches to healthcare, such as personalised and precision medicine (Hey et al., 2009, Collins, 2010, Hood & Friend, 2011).

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