GWAS summary data

Hill, W.D., et al. (In Press). Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income. Nature Communications. [dataset]

Hill, W.D., et al. (2019). Genetic contributions to two special factors of neuroticism are associated with affluence, higher intelligence, better health, and longer life. Molecular Psychiatry. [dataset]

Luciano, M., et al. (2019). The influence of X chromosome variants on trait neuroticism. Molecular Psychiatry. [dataset]

Davies, G., et al. (2018). Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nature Communications, 9(1), 1-16 2098. [dataset]

Deary, V., et al. (2018). Genetic contributions to self-reported tiredness. Molecular Psychiatry, 23(3), 609-620. [dataset]

Luciano, M., et al. (2018). Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism. Nature Genetics, 50(1), 6-11. [dataset]

Hagenaars, S.P., et al. (2017). Genetic prediction of male pattern baldness. PLOS Genetics, 13(2), e1006594. [dataset]

Harris, S.E., et al. (2017). Molecular genetic contributions to self-rated health. International Journal of Epidemiology, 46(3), 994-1009. [dataset]

Hill, W.D., et al. (2016). Molecular genetic contributions to social deprivation and household income in UK Biobank. Current Biology, 26(22), 3083-3089. [dataset]

Davies, G., et al. (2016). Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151). Molecular Psychiatry, 21(6), 758-767. [dataset]

Deary, I.J., et al. (2011). A free, easy-to-use, copmuter-based simple and four-choice reaction time programme: The Deary-Liewald reaction time task. Behavior Research Methods, 43(1), 258-268. [software]