Data Descriptor: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
(2017) In Scientific Data 4.- Abstract
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ∼82 K... (More)
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ∼82 K Europeans via the exome chip, and ∼90% of low-frequency non-coding variants in ∼44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D. © The Author(s) 2017. (Less)
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- author
- organization
-
- EXODIAB: Excellence of Diabetes Research in Sweden
- EpiHealth: Epidemiology for Health
- Genetic and Molecular Epidemiology (research group)
- Translational Muscle Research (research group)
- Diabetic Complications (research group)
- Diabetes - Islet Patophysiology (research group)
- Cardiovascular Research - Hypertension (research group)
- Department of Clinical Sciences, Malmö
- Diabetes - Cardiovascular Disease (research group)
- Internal Medicine - Epidemiology (research group)
- publishing date
- 2017
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Scientific Data
- volume
- 4
- article number
- 170179
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85038860473
- pmid:29257133
- wos:000418568400001
- ISSN
- 2052-4463
- DOI
- 10.1038/sdata.2017.179
- language
- English
- LU publication?
- yes
- additional info
- Export Date: 3 January 2018
- id
- 7f2d7fd8-9349-4419-8351-3b2e399004ab
- date added to LUP
- 2018-01-03 10:03:30
- date last changed
- 2024-05-13 01:36:57
@article{7f2d7fd8-9349-4419-8351-3b2e399004ab, abstract = {{To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ∼82 K Europeans via the exome chip, and ∼90% of low-frequency non-coding variants in ∼44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D. © The Author(s) 2017.}}, author = {{Flannick, Jason and Fuchsberger, Christian and Mahajan, Anubha and Teslovich, Tanya M and Agarwala, Vineeta and Gaulton, Kyle and V Varga, Tibor and Franks, Paul and Fadista, Joao and Kravic, Jasmina and Lyssenko, Valeriya and Ladenvall, Claes and Rosengren, Anders and Groop, Leif and Melander, Olle and Orho-Melander, Marju and Nilsson, Peter}}, issn = {{2052-4463}}, language = {{eng}}, publisher = {{Nature Publishing Group}}, series = {{Scientific Data}}, title = {{Data Descriptor: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls}}, url = {{http://dx.doi.org/10.1038/sdata.2017.179}}, doi = {{10.1038/sdata.2017.179}}, volume = {{4}}, year = {{2017}}, }