The big data revolution and human genetics

The big data revolution and human genetics Human Molecular Genetics, 2018, Vol. 27, No. R1 R1 doi: 10.1093/hmg/ddy123 Advance Access Publication Date: 16 April 2018 Editorial Editorial The concept of ‘Big Data’ is now ubiquitous. Virtually all major in- that a goal of contemporary human genetics research is to incorpo- dustries, whether associated with finance, banking, marketing, rate genetic information into clinical care. Unfortunately, combin- ing genetic data with routine clinical data is fraught with difficulties retail, social media, energy or manufacturing, have embraced the given that clinical data are often ‘noisy’ (e.g. physician hand-written analysis of big data sets hoping to obtain insights that could im- notes, different ways of measuring clinical parameters entered prove efficiency and create better products. It is no surprise then into patient’s record, etc.). Altman and colleagues describe efforts to that the health care, biomedical research and, in particular, hu- identify clinically meaningful relationships between genetic var- man genetics communities have also embraced big data initia- iants and responses to drugs used to treat various conditions; tives. However, creating and analysing large-scale data sets is not whereas Wolford and colleagues, Diao and colleagues, Ohno- particularly new in human genetics research contexts, since a Machado and colleagues and Glicksberg and colleagues all consider single human genome contains 23.2 billion nucleotides worth general integrated analysis of clinical data and genetic data with an of information. Just how these nucleotides are organized as genes eye towards improving health based on the insights obtained from and their associated regulatory elements, lead to particular func- such analyses. Pushing things even further, Huentelman and tions, and interact, is as complicated and fascinating a big data Talboom consider integrating genetic information with data beyond analysis exercise as any in science. What is becoming more fre- that routinely collected in the clinic and consider health data col- quent, however, is the coupling or integration of human genetic lected with wearable wireless devices, health data derived from so- data with other data types, essentially adding to the already very cial media, and data obtained from other modalities associated large data sets human genetic researchers are willing and eager with the ‘internet of things’. Ioannides and Khoury consider ques- to analyse. This issue of Human Molecular Genetics is devoted to tions about how we, as a scientific community, can test and prove reviews of efforts to both mine the big data inherent in human the utility of insights obtained from big genetic data initiatives. genomes and integrate that data with other data types to ad- Finally, Middelton provides insight into how consumers of big ge- vance genetically oriented biomedical science and health care. netic data, and the insights that the analysis of those data will pro- Given the fundamental manner in which elements in DNA im- duce, might react to their use and availability. Given that more and pact human physiology and mediate pathogenic processes, there more data will be collected on individuals at an ever-increasing are an unlimited number of settings in which human genetic re- pace, big genetic data and other big data types, will not go away. It search could complement, and be combined with, data from other will therefore be fascinating to see, as these reviews anticipate, just research areas, as these reviews make clear. Virtually all of the how such data will be used to effect positive changes to biomedical reviews consider combining genetic data with other data to iden- science, health care and society as a whole. tify associations and connections between naturally occurring ge- netic variants possessed by individuals and phenotypes of all Conflict of Interest statement. None declared. sorts, most notably those that may have clinical and public health utility. Telenti and colleagues consider the development and application of bioinformatics and data analysis tools to interpret Funding variationinthe humangenomeand show that by combining Dr. Schork and his lab are supported in part by US National thousands of human genomes for analysis, insights into the likely Institutes of Health Grants UL1TR001442 (CTSA), U24AG051129, functional effects of genetic variants can be found. Scheuermann U19G023122, as well as the Translational Genomics Research and colleagues discuss methodology for leveraging what amounts Institute (note that the content of this manuscript is solely the to the billions of bits of information in the human genome to cata- responsibility of the authors and does not necessarily represent logue, characterize and subdivide the potentially trillions of cells the official views of the NIH). in the human body. Fan and colleagues consider combining ge- netic data with imaging data, in particular neuroimaging data, in Nicholas J. Schork order to derive insights into human brain morphology that genetic and imaging data alone would not allow. The Translational Genomics Research Institute, Phoenix, AZ 85004, USA Combining genetic data on patients in health systems with clin- ical information routinely collected on them is very logical given Email: nschork@tgen.org V The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com R1 Downloaded from https://academic.oup.com/hmg/article-abstract/27/R1/R1/4973001 by Ed 'DeepDyve' Gillespie user on 16 June 2018 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Human Molecular Genetics Oxford University Press

The big data revolution and human genetics

Human Molecular Genetics , Volume Advance Article (R1) – Apr 16, 2018
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Abstract

Human Molecular Genetics, 2018, Vol. 27, No. R1 R1 doi: 10.1093/hmg/ddy123 Advance Access Publication Date: 16 April 2018 Editorial Editorial The concept of ‘Big Data’ is now ubiquitous. Virtually all major in- that a goal of contemporary human genetics research is to incorpo- dustries, whether associated with finance, banking, marketing, rate genetic information into clinical care. Unfortunately, combin- ing genetic data with routine clinical data is fraught with difficulties retail, social media, energy or manufacturing, have embraced the given that clinical data are often ‘noisy’ (e.g. physician hand-written analysis of big data sets hoping to obtain insights that could im- notes, different ways of measuring clinical parameters entered prove efficiency and create better products. It is no surprise then into patient’s record, etc.). Altman and colleagues describe efforts to that the health care, biomedical research and, in particular, hu- identify clinically meaningful relationships between genetic var- man genetics communities have also embraced big data initia- iants and responses to drugs used to treat various conditions; tives. However, creating and analysing large-scale data sets is not whereas Wolford and colleagues, Diao and colleagues, Ohno- particularly new in human genetics research contexts, since a Machado and colleagues and Glicksberg and colleagues all consider single human genome contains 23.2 billion nucleotides worth general integrated analysis of clinical data and genetic data with an of information. Just how these nucleotides are organized as genes eye towards improving health based on the insights obtained from and their associated regulatory elements, lead to particular func- such analyses. Pushing things even further, Huentelman and tions, and interact, is as complicated and fascinating a big data Talboom consider integrating genetic information with data beyond analysis exercise as any in science. What is becoming more fre- that routinely collected in the clinic and consider health data col- quent, however, is the coupling or integration of human genetic lected with wearable wireless devices, health data derived from so- data with other data types, essentially adding to the already very cial media, and data obtained from other modalities associated large data sets human genetic researchers are willing and eager with the ‘internet of things’. Ioannides and Khoury consider ques- to analyse. This issue of Human Molecular Genetics is devoted to tions about how we, as a scientific community, can test and prove reviews of efforts to both mine the big data inherent in human the utility of insights obtained from big genetic data initiatives. genomes and integrate that data with other data types to ad- Finally, Middelton provides insight into how consumers of big ge- vance genetically oriented biomedical science and health care. netic data, and the insights that the analysis of those data will pro- Given the fundamental manner in which elements in DNA im- duce, might react to their use and availability. Given that more and pact human physiology and mediate pathogenic processes, there more data will be collected on individuals at an ever-increasing are an unlimited number of settings in which human genetic re- pace, big genetic data and other big data types, will not go away. It search could complement, and be combined with, data from other will therefore be fascinating to see, as these reviews anticipate, just research areas, as these reviews make clear. Virtually all of the how such data will be used to effect positive changes to biomedical reviews consider combining genetic data with other data to iden- science, health care and society as a whole. tify associations and connections between naturally occurring ge- netic variants possessed by individuals and phenotypes of all Conflict of Interest statement. None declared. sorts, most notably those that may have clinical and public health utility. Telenti and colleagues consider the development and application of bioinformatics and data analysis tools to interpret Funding variationinthe humangenomeand show that by combining Dr. Schork and his lab are supported in part by US National thousands of human genomes for analysis, insights into the likely Institutes of Health Grants UL1TR001442 (CTSA), U24AG051129, functional effects of genetic variants can be found. Scheuermann U19G023122, as well as the Translational Genomics Research and colleagues discuss methodology for leveraging what amounts Institute (note that the content of this manuscript is solely the to the billions of bits of information in the human genome to cata- responsibility of the authors and does not necessarily represent logue, characterize and subdivide the potentially trillions of cells the official views of the NIH). in the human body. Fan and colleagues consider combining ge- netic data with imaging data, in particular neuroimaging data, in Nicholas J. Schork order to derive insights into human brain morphology that genetic and imaging data alone would not allow. The Translational Genomics Research Institute, Phoenix, AZ 85004, USA Combining genetic data on patients in health systems with clin- ical information routinely collected on them is very logical given Email: nschork@tgen.org V The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com R1 Downloaded from https://academic.oup.com/hmg/article-abstract/27/R1/R1/4973001 by Ed 'DeepDyve' Gillespie user on 16 June 2018

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Human Molecular GeneticsOxford University Press

Published: Apr 16, 2018

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