Difference between revisions of "Journal:Building infrastructure for African human genomic data management"
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'''Keywords''': genomic data, data archive, H3Africa data, African genomic data | '''Keywords''': genomic data, data archive, H3Africa data, African genomic data | ||
==Introduction== | |||
Advances in high-throughput [[Genomics|genomic]] technologies are laying the foundations for the goal of precision medicine to be realized.<ref name="ChristensenAssessing15">{{cite journal |title=Assessing the Costs and Cost-Effectiveness of Genomic Sequencing |journal=Journal of Personalized Medicine |author=Christensen, K.D.; Dukhovny, D.; Siebert, U. et al. |volume=5 |issue=4 |pages=470–86 |year=2015 |doi=10.3390/jpm5040470 |pmid=26690481 |pmc=PMC4695866}}</ref><ref name="AronsonBuilding15">{{cite journal |title=Building the foundation for genomics in precision medicine |journal=Nature |author=Aronson, S.J.; Rehm, H.L. |volume=526 |issue=7573 |pages=336–42 |year=2015 |doi=10.1038/nature15816 |pmid=26469044 |pmc=PMC5669797}}</ref> Decreasing costs and the capacity to generate larger volumes of human genomic data at faster rates are enabling population-level genomics studies to be conducted. (Goldfeder et al. 2017; Prokop et al. 2018) However, most of the current population-level genomics studies and data generated to date have a significant population representational bias, with the majority of genome sequences being derived from European and North American ancestry, regions that have been early adopters of genomic technologies. (Popejoy and Fullerton 2016; Prokop et al. 2018) African researchers, in general, have been late adopters of high-throughput technologies for use in population genomics due to more limited resources and funding. To address this critical gap in scientific knowledge about African genomics and population variation, and inspired by the African Society for Human Genetics, the [[National Institutes of Health]] (NIH) and The Wellcome Trust, through the Human Hereditary and Health in Africa (H3Africa) program, have funded multiple genomics projects led by African investigators. (H3Africa Consortium et al. 2014; Mulder et al. 2018) To support the H3Africa projects in terms of provisioning of infrastructure for secure data storage, management, and computing, the NIH has also funded a Pan-African [[Bioinformatics]] Network for H3Africa ([http://www.h3abionet.org H3ABioNet]). (Mulder et al. 2016) | |||
==References== | ==References== | ||
Revision as of 19:41, 11 November 2019
| Full article title | Building infrastructure for African human genomic data management |
|---|---|
| Journal | Data Science Journal |
| Author(s) | Parker, Ziyaad; Maslamoney, Suresh; Meintjes, Ayton; Botha, Gerrit; Panji, Sumir; Hazelhurst, Scott; Mulder, Nicola |
| Author affiliation(s) | University of Cape Town, University of the Witwatersrand |
| Primary contact | Email: ziyaad dot parker at uct dot ac dot za |
| Year published | 2019 |
| Volume and issue | 18(1) |
| Page(s) | 47 |
| DOI | 10.5334/dsj-2019-047 |
| ISSN | 1683-1470 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://datascience.codata.org/articles/10.5334/dsj-2019-047/ |
| Download | https://datascience.codata.org/articles/10.5334/dsj-2019-047/galley/894/download/ (PDF) |
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This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
Human genomic data are large and complex, and require adequate infrastructure for secure storage and transfer. The National Institutes of Health (NIH) and The Wellcome Trust have funded multiple projects on genomic research, including the Human Heredity and Health in Africa (H3Africa) initiative, and data are required to be deposited into the public domain. The European Genome-phenome Archive (EGA) is a repository for sequence and genotype data where data access is controlled by access committees. Access is determined by a formal application procedure for the purpose of secure storage and distribution, which must be in line with the informed consent of the study participants. H3Africa researchers based in Africa and generating their own data can benefit tremendously from the data sharing capabilities of the internet by using the appropriate technologies. The H3Africa Data Archive is an effort between the H3Africa data generating projects, H3ABioNet, and the EGA to store and submit genomic data to public repositories. H3ABioNet maintains the security of the H3Africa Data Archive, ensures ethical security compliance, supports users with data submission, and facilitates data transfers. The goal is to ensure efficient data flow between researchers, the archive, and the EGA or other public repositories. To comply with the H3Africa data sharing and release policy, nine months after the data is in secure storage, H3ABioNet converts the data into an Extensible Markup Language (XML) format ready for submission to EGA. This article describes the infrastructure that has been developed for African human genomic data management.
Keywords: genomic data, data archive, H3Africa data, African genomic data
Introduction
Advances in high-throughput genomic technologies are laying the foundations for the goal of precision medicine to be realized.[1][2] Decreasing costs and the capacity to generate larger volumes of human genomic data at faster rates are enabling population-level genomics studies to be conducted. (Goldfeder et al. 2017; Prokop et al. 2018) However, most of the current population-level genomics studies and data generated to date have a significant population representational bias, with the majority of genome sequences being derived from European and North American ancestry, regions that have been early adopters of genomic technologies. (Popejoy and Fullerton 2016; Prokop et al. 2018) African researchers, in general, have been late adopters of high-throughput technologies for use in population genomics due to more limited resources and funding. To address this critical gap in scientific knowledge about African genomics and population variation, and inspired by the African Society for Human Genetics, the National Institutes of Health (NIH) and The Wellcome Trust, through the Human Hereditary and Health in Africa (H3Africa) program, have funded multiple genomics projects led by African investigators. (H3Africa Consortium et al. 2014; Mulder et al. 2018) To support the H3Africa projects in terms of provisioning of infrastructure for secure data storage, management, and computing, the NIH has also funded a Pan-African Bioinformatics Network for H3Africa (H3ABioNet). (Mulder et al. 2016)
References
- ↑ Christensen, K.D.; Dukhovny, D.; Siebert, U. et al. (2015). "Assessing the Costs and Cost-Effectiveness of Genomic Sequencing". Journal of Personalized Medicine 5 (4): 470–86. doi:10.3390/jpm5040470. PMC PMC4695866. PMID 26690481. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4695866.
- ↑ Aronson, S.J.; Rehm, H.L. (2015). "Building the foundation for genomics in precision medicine". Nature 526 (7573): 336–42. doi:10.1038/nature15816. PMC PMC5669797. PMID 26469044. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5669797.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original paper listed references alphabetically; this wiki lists them by order of appearance, by design. The two footnotes were turned into inline references for convenience.
