Published July 21, 2025
| Version v2
Dataset
Open
GWAS summary statistics for self-reported high cholesterol (UK Biobank Data-Field 20002; Coding 1473)
Description
GWAS summary statistics for self-reported high cholesterol in the UK Biobank (Data-Field 20002; Coding 1473), output by PLINK2 software.
This includes:
- P-values for each SNP (three rows per SNP, ordered by additive test
TEST = "ADD";
dominance testTEST = "DOMDEV"
and the 2-df joint testTEST = "GENO_2DF"
), obtained from the genotypic model where both additive and dominance effects are included
(file:bri_result_high_chol.self_reported_cholesterol.glm.logistic.hybrid
). and -
P-values for each SNP from the traditional additive test, where the model is additive-only
(file:bri_result_high_chol_additive.self_reported_cholesterol.glm.logistic.hybrid
).
Please note that for the traditional additive GWAS result, one should refer to the second file, not to the first file (where TEST = "ADD"
).
Each variable (column) in the PLINK2 summary is interpreted as the following:
- #CHROM: The chromosome number.
- POS: GRCh37 position.
- ID: The SNP ID.
- REF: Reference Allele.
- ALT: Alternate Allele.
- A1: The Effect Allele.
- FIRTH?: Whether to use the Firth implementation for the logistic regression.
- TEST: Indication of the type of hypothesis test to perform ("GENO_2DF": joint test; "DOMDEV": dominance test; "ADD": additive test)
- OBS_CT: Number of samples included in the analysis.
- OR: Odds ratio.
- LOG(OR)_SE: Standard error of the log odds ratio.
- (first file) Z_OR_F_STAT: Wald Statistics for the 1-df test (TEST = "
DOMDEV
" or "ADD
") and the 2-df test (TEST = "GENO_2DF
"). - (second file) Z_STAT: Z Statistics for the test.
- P: P-value for the test.
- ERRCODE: Error code ("." means no error).
Files
Files
(196.2 MB)
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md5:7abf168ee4085bf645bbf71547ac8839
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146.1 MB | Download |
md5:dda02e74f2213e24ada72476841818f0
|
50.1 MB | Download |
Additional details
References
- Zhang Z, Lawless JF, Paterson AD, Sun L. Detecting latent gene-environment interaction when analyzing binary traits. bioRxiv. 2024.07.10.602954. doi: 10.1101/2024.07.10.602954