1. Binary phenome analysis
Using SAIGE, we have analyzed ~1,400 UKBiobank Phecode binary phenotypes (400,000 White British samples) on 28 million imputed variants. All analysis summary statistics are available from the following link.
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Pheweb (all phewebs in UMich): link
Acknowledgment: The analysis was done in collaboration with Dr. Willer and Dr. Abecasis groups. The Pheweb was created by Dr. Abecasis
group.
2. Categorical phenotype analysis
POLMM (Proportional Odds Logistic Mixed Model) approaches are designed for ordinal categorical data analysis in large cohort studies. For UK Biobank data analysis (on 258 ordinal categorical phenotypes including 150 food and other preferences), we use a sparse GRM to adjust for sample relatedness.
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Pheweb: link
1. UK-Biobank 200K WES
Using SAIGE-GENE+, we analyzed UK-Biobank 200K WES data for 30 quantitative and 141 binary phenotypes.
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PheWEB-like visual server for summary statistics
2. UK-Biobank Imputed data analysis
Using SAIGE-GENE, we have carried out gene-based rare variant test (MAF < 0.01) for 53 UKBiobank quantitative phenotypes (400,000 White British samples). Missense and stop-gain variants were used in the analysis. The association test p-value are available from the following link.
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Summary statistics
3. UK-Biobank 50K WES, Binary Phenome Analysis
Using robust SKAT-O approach for binary phenotypes, we analyzed UK-Biobank WES data for 791 binary phenotypes.
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PheWEB-like visual server for summary statistics
Using SPAGE, we have carried out GxE analysis for 80 selected phenotype x environment combinations. The association test p-value are available from the following link.
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Summary statistics
Using Gauss, we carried out gene-set association analysis using UK-Biobank SAIGE results
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PheWEB-like visual server for summary statistics
Using SPACox, we have carried out GWAS survival analysis for 13 selected phenotypes. The association test p-value are available from the following link.
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Summary statistics
GWAS analysis results for 76 phenotypes in Korean Biobank (KoGES)
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PheWEB-like visual server for summary statistics