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The fine-mapped associations of 35 lab biomarkers described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'

dataset
posted on 19.06.2020 by Yosuke Tanigawa, Nasa Sinnott-Armstrong, Christian Benner, Manuel Rivas

The dataset contains the output from FINEMAP, a software to identify causal variants from genome-wide association 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.

For each trait, we provide a tar archive file which contains the full output from FINEMAP for the regions with at least one genome-wide significant associations (p < 5e-9) from the multi-ethnic GWAS meta-analysis within UK Biobank. The content of the tar archive is organized by directories, named as chr[CHROM]/[TRAIT]/range[RANGE], and contains the following files:

  • GLOBAL_[TRAIT]_chr[CHROM]_range[RANGE].bdose.zst
  • GLOBAL_[TRAIT]_chr[CHROM]_range[RANGE].config.zst
  • GLOBAL_[TRAIT]_chr[CHROM]_range[RANGE].cred.zst
  • GLOBAL_[TRAIT]_chr[CHROM]_range[RANGE].ld.zst
  • GLOBAL_[TRAIT]_chr[CHROM]_range[RANGE].master.zst
  • GLOBAL_[TRAIT]_chr[CHROM]_range[RANGE].snp.zst
  • GLOBAL_[TRAIT]_chr[CHROM]_range[RANGE].z.zst

where,

  • [TRAIT]: trait name
  • [CHROM]: chromosome
  • [RANGE]: the range of the region in the format of [start position]-[end position].

We provide the list of traits and regions included in this data release in FINEMAP.index.tsv. This is a flat table with 3 columns:

  • trait: the biomarker trait
  • chr: chromosome
  • range: the range

Note that we used GRCh37/hg19 genome reference in the analysis and the BETA is always reported for the alternate allele.

Please check the FINEMAP paper and software documentation for the detailed explanation of the file formats.

  • Benner, C. et al. FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics 32, 1493–1501 (2016).
  • Christian Benner. FINEMAP. http://christianbenner.com/.

Also, all the files in the tar archive is compressed with Zstandard (as indicated by the .zst extension). You can check the contents with zstdcat command and uncompress the files with zstd -d [file.zst]. The Zstandard software can be built from source, or simply available from conda (https://anaconda.org/conda-forge/zstd), pip (https://pypi.org/project/zstd/) or brew (https://formulae.brew.sh/formula/zstd). Please check Zstandard website (http://facebook.github.io/zstd/) for more information.

Funding

SOFTWARE FOR LARGE-SCALE INFERENCE OF THE GENETICS OF LIFESTYLE MEASURES, BIOMARKERS, AND COMMON AND RARE DISEASES

National Human Genome Research Institute

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  • HG - National Human Genome Research Institute (NHGRI)

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