GWAS summary statistics for Five UK Biobank phenotypes used in covImpute

This repository contains genome-wide association study (GWAS) summary statistics used in the paper:

“Domain-Aware Matrix Completion for Phenotype Imputation Using Electronic Health Record Data with Applications in Genomic Research”
(Annals of Applied Statistics).

The repository includes GWAS summary statistics derived from the UK Biobank for five phenotypes:

• severe depression (MDD)

• breast cancer (BrCa)

• prostate cancer (PrCa)

• high blood pressure (HTN)

• bowel cancer (CRC)

For each phenotype, GWAS summary statistics are provided for five analysis approaches:

• COVV3C: covImpute

• LTPI: LTPI

• SOFT: softImpute

• AUTO: autoComplete

• GWAS: GWAS based on observed case-control status

In total, the repository contains 25 GWAS summary statistic files.

These summary statistics were used in the real-data analyses to compare the imputation performance of matrix completion methods and to evaluate their impact on downstream genomic analyses.

Each file contains SNP-level GWAS summary statistics with the following columns:

• CHROM: chromosome (hg19)

• GENPOS: genomic position (hg19)

• ID: SNP identifier in the format CHR-GENPOS-ALLELE0-ALLELE1

• ALLELE1: effect allele

• ALLELE0: non-effect allele

• BETA: effect size estimate

• SE: standard error

• LOG10P: p-value on the log10 scale

• N: sample size

• TEST: REGENIE output field indicating the analysis type

All variants are aligned to the hg19 genome build used in the analyses described in the paper.

The file names follow the convention:

<Phenotype>_<Method>.txt.gz

Examples include:

• Severe_depression_COVV3C.txt.gz

• Breast_cancer_LTPI.txt.gz

• Prostate_cancer_SOFT.txt.gz

• High_blood_pressure_AUTO.txt.gz

• Bowel_cancer_GWAS.txt.gz