The meta-analyzed GWAS summary statistics for 35 lab biomarkers described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'

The dataset contains meta-analyzed GWAS summary statistics for 35 biomarker traits described in the following preprint:<br>N. Sinnott-Armstrong*, Y. Tanigawa*, et al, Genetics of 38 blood and urine biomarkers in the UK Biobank. bioRxiv, 660506 (2019). doi:10.1101/660506<br><br>Note that we are preparing a revised version of the manuscript and this dataset contains 35 (instead of 38) biomarker phenotypes.<br><br>We provide the list of 35 biomarkers in "list_of_35_biomarkers.tsv". We used the "Phenotype_name" column in this table for the file names. For each phenotype, we provide two compressed tab-delimited files, named "[Phenotype_name].array.gz" and "[Phenotype_name].imp.gz", which contain the summary statistics for genetic variants on the genotyping array and the imputed dataset, respectively.<br><br>We used METAL for the meta-analysis for 4 populations (White British, non-British White, African, and South Asian) within UK Biobank. The files have the following columns: CHROM: the chromosomePOS: the positionMarkerName: the variant identifierREF: the reference alleleALT: the alternate alleleEffect: the effect size (BETA) estimateStdErr: the standard error of effect size estimateP-value: the p-value of the associationDirection: the direction of effect sizeHetISq, HetChiSq, HetDf, HetPVal: heterogeneity statistics from METAL Note that we used GRCh37/hg19 genome reference in the analysis and the BETA is always reported for the alternate allele.<br><br>Please also check the METAL documentation (https://genome.sph.umich.edu/wiki/METAL_Documentation).<br><br>The summary statistic files are compressed with <code>bgzip</code> and indexed with <code>tabix</code> (the <code>.tbi</code> files). One should be able to read those files with the standard <code>gzip</code>/<code>zcat</code>.