Phenome-wide association studies across large population cohorts support drug target validation
收藏资源简介：
Summary-level data generated by Genomics plc as presented in:<br> Diogo, D. et al. Phenome-wide association studies across large population cohorts support drug target validation. Nat. Commun. 9, 4285 (2018). https://doi.org/10.1038/s41467-018-06540-3 If you have any questions or comments regarding these files, please contact Genomics plc at research@genomicsplc.com NOTES<br> -----------------------------<br> These analyses were carried out using the interim UK Biobank imputation data release. Analyses were restricted to a subset of "white-British" unrelated samples with a maximum sample size of 112,337 individuals. Case control phenotypes were defined based on categorical datafields as listed in the accompanying file. <br> Quantitative phenotypes were either rank-normalised before analysis, or beta/se values were standardised after analysis using the variance of the phenotype. The normalisation value is indicated in the accompanying file.<br> <br> All analyses included Age at assessment, sex, genotyping chip, and 10 principal components as covariates. We used plink1.9 linear/logistic regression as appropriate. For chromosome X variants males were treated as having 0 or 2 alternative alleles. The results are not adjusted for genomic control. DATA FILE CONTENT DESCRIPTION<br> -----------------------------<br> CHR - Chromosome<br> SNP - Variant rsID<br> ALT - Alternative allele (effect allele)<br> REF - Reference Allele (non-effect allele)<br> BP - Position in base pairs (b37, 1-based)<br> NMISS - Number of samples with non-missing genotypes<br> BETA - Effect size (log odds ratio or standardised effect size)<br> SE - Standard error<br> P - P-value<br> F_MISS - genotype missing rate<br> P_hwe - Hardy-weinberg p-value<br> MAF - ALT allele frequency
