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The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants.

Fadista, Joao LU ; Manning, Alisa K; Florez, Jose C and Groop, Leif LU (2016) In European Journal of Human Genetics 24. p.1202-1205
Abstract
Genome-wide association studies (GWAS) have long relied on proposed statistical significance thresholds to be able to differentiate true positives from false positives. Although the genome-wide significance P-value threshold of 5 × 10(-8) has become a standard for common-variant GWAS, it has not been updated to cope with the lower allele frequency spectrum used in many recent array-based GWAS studies and sequencing studies. Using a whole-genome- and -exome-sequencing data set of 2875 individuals of European ancestry from the Genetics of Type 2 Diabetes (GoT2D) project and a whole-exome-sequencing data set of 13 000 individuals from five ancestries from the GoT2D and T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation... (More)
Genome-wide association studies (GWAS) have long relied on proposed statistical significance thresholds to be able to differentiate true positives from false positives. Although the genome-wide significance P-value threshold of 5 × 10(-8) has become a standard for common-variant GWAS, it has not been updated to cope with the lower allele frequency spectrum used in many recent array-based GWAS studies and sequencing studies. Using a whole-genome- and -exome-sequencing data set of 2875 individuals of European ancestry from the Genetics of Type 2 Diabetes (GoT2D) project and a whole-exome-sequencing data set of 13 000 individuals from five ancestries from the GoT2D and T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) projects, we describe guidelines for genome- and exome-wide association P-value thresholds needed to correct for multiple testing, explaining the impact of linkage disequilibrium thresholds for distinguishing independent variants, minor allele frequency and ancestry characteristics. We emphasize the advantage of studying recent genetic isolate populations when performing rare and low-frequency genetic association analyses, as the multiple testing burden is diminished due to higher genetic homogeneity.European Journal of Human Genetics advance online publication, 6 January 2016; doi:10.1038/ejhg.2015.269. (Less)
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type
Contribution to journal
publication status
published
subject
in
European Journal of Human Genetics
volume
24
pages
1202 - 1205
publisher
Nature Publishing Group
external identifiers
  • pmid:26733288
  • scopus:84953318772
  • wos:000380390300020
ISSN
1476-5438
DOI
10.1038/ejhg.2015.269
language
English
LU publication?
yes
id
3241ab93-fd93-4fbb-905c-178a06ddf56e (old id 8592999)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/26733288?dopt=Abstract
date added to LUP
2016-02-01 21:38:13
date last changed
2017-10-22 04:50:57
@article{3241ab93-fd93-4fbb-905c-178a06ddf56e,
  abstract     = {Genome-wide association studies (GWAS) have long relied on proposed statistical significance thresholds to be able to differentiate true positives from false positives. Although the genome-wide significance P-value threshold of 5 × 10(-8) has become a standard for common-variant GWAS, it has not been updated to cope with the lower allele frequency spectrum used in many recent array-based GWAS studies and sequencing studies. Using a whole-genome- and -exome-sequencing data set of 2875 individuals of European ancestry from the Genetics of Type 2 Diabetes (GoT2D) project and a whole-exome-sequencing data set of 13 000 individuals from five ancestries from the GoT2D and T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) projects, we describe guidelines for genome- and exome-wide association P-value thresholds needed to correct for multiple testing, explaining the impact of linkage disequilibrium thresholds for distinguishing independent variants, minor allele frequency and ancestry characteristics. We emphasize the advantage of studying recent genetic isolate populations when performing rare and low-frequency genetic association analyses, as the multiple testing burden is diminished due to higher genetic homogeneity.European Journal of Human Genetics advance online publication, 6 January 2016; doi:10.1038/ejhg.2015.269.},
  author       = {Fadista, Joao and Manning, Alisa K and Florez, Jose C and Groop, Leif},
  issn         = {1476-5438},
  language     = {eng},
  month        = {01},
  pages        = {1202--1205},
  publisher    = {Nature Publishing Group},
  series       = {European Journal of Human Genetics},
  title        = {The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants.},
  url          = {http://dx.doi.org/10.1038/ejhg.2015.269},
  volume       = {24},
  year         = {2016},
}