0000000000419127
AUTHOR
Arcadi Navarro
Assessing statistical significance in multivariable genome wide association analysis
Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS. Results: We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P-values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whe…
The genome sequencing of an albino Western lowland gorilla reveals inbreeding in the wild
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License.-- et al.
Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate
Abstract Under the multiple testing framework, we propose the multiplicity- and dependency-adjustment method (MADAM) which transforms test statistics into adjusted p -values for control of the family-wise error rate. For demonstration, we apply the MADAM to data from a genetic association study.
Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies
Mieth, Bettina et al.
Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences1
AbstractHumans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to stro…