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:
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
Note that we are preparing a revised version of the manuscript and this dataset contains 35 (instead of 38) biomarker phenotypes.
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,
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 chromosome
- POS: the position
- MarkerName: the variant identifier
- REF: the reference allele
- ALT: the alternate allele
- Effect: the effect size (BETA) estimate
- StdErr: the standard error of effect size estimate
- P-value: the p-value of the association
- Direction: the direction of effect size
- HetISq, 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.
Please also check the METAL documentation (https://genome.sph.umich.edu/wiki/METAL_Documentation).
The summary statistic files are compressed with
bgzip and indexed with
.tbi files). One should be able to read those files with the standard
SOFTWARE FOR LARGE-SCALE INFERENCE OF THE GENETICS OF LIFESTYLE MEASURES, BIOMARKERS, AND COMMON AND RARE DISEASES
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