# UK_Biobank_GWAS

**Repository Path**: khjia/UK_Biobank_GWAS

## Basic Information

- **Project Name**: UK_Biobank_GWAS
- **Description**: Overview of the data QC, code, and GWAS summary output from the 2017 UK Biobank data release
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2020-07-12
- **Last Updated**: 2021-02-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Table of Contents
* [Updates](#updates) 
* [imputed-v3 Phenotypes](#imputed-v3-phenotypes)
* [imputed-v3 Sample QC](#imputed-v3-sample-qc)
* [imputed-v3 Variant QC](#imputed-v3-variant-qc)
* [imputed-v3 Association model](#imputed-v3-association-model)

### Updates

With the re-release of UK Biobank genotype imputation (which we term imputed-v3), we have generated an updated set of GWAS summary statistics for the genetics community. 
  * Increased the number of phenotypes with application UKB31063 and addtl. custom curated phenotypes (see imputed-v3 Phenotypes)
  * More liberal inclusion of samples (see imputed-v3 Sample QC)
  * Inclusion of more SNPs (see imputed-v3 Variant QC)
  * Updates to our association model (imputed-v3 Association model)
Our largest change is that for all phenotypes, we have run a female-only and male-only GWAS along with the full set.

Information and scripts from the previous round of GWAS are available in the [imputed-v2-gwas](https://github.com/Nealelab/UK_Biobank_GWAS/tree/master/imputed-v2-gwas) subdirectory

### imputed-v3 Phenotypes

  * Auto-curated phenotypes using PHESANT: 
    * Source repository: https://github.com/MRCIEU/PHESANT
    * Customized PHESANT repository: https://github.com/astheeggeggs/PHESANT
  * ICD10 codes (all non-coded individuals treated as controls)
  * Curated phenotypes in collaboration with the [FinnGen consortium](https://www.finngen.fi/)

  * Phenotypes in both sexes
    * PHESANT: 2891 total (274 continuous / 271 ordinal / 2346 binary)
    * ICD10: 633 binary
    * FinnGen curated: 559

  * Phenotypes in females
    * PHESANT: 2393 total (259 continuous / 257 ordinal / 1877 binary)
    * ICD10: 482 binary
    * FinnGen curated: 412

  * Phenotypes in males   
    * PHESANT: 2305 total (262 continuous / 259 ordinal / 1784 binary)
    * ICD10: 439 binary
    * FinnGen curated: 400

  * Unique PHESANT phenotypes: 3011, of which 274 are continuous
  * 4203 total unique phenotypes: 3011 PHESANT + 559 finngen + 633 ICD10

  * Summary files: 
	* **phenotypes.both_sexes.tsv.gz** 
	* **phenotypes.female.tsv.gz** 
	* **phenotypes.male.tsv.gz**
    * phenotype - phenotype ID
    * description - short description of phenotype
    * source - PHESANT auto-curation, ICD10, or FinnGen
    * n_controls - number of QC positive samples responding negatively to phenotype designation (NA if quantitative)
    * n_cases - number of QC positive samples responding affirmatively to phenotype designation (NA if quantitative)
    * n_missing - number of missing QC positive samples
    * n_non_missing - number of non-missing QC positive samples

### imputed-v3 Sample QC

  * __imputed-v3 parameters__
	* Used.in.pca.calculation filter (unrelated samples)
	* sex chromosome aneuploidy filter
	* Use provided PCs for European sample selection to determine British ancestry
	  * Use 7 standard deviations away from the 1st 6 PCs
	  * Further Filter to self-reported 'white-British' / 'Irish' / 'White'
	* **QCed sample count: 361194 samples** 
  * __imputed-v2 parameters__
    * Used.in.pca.calculation filter (unrelated samples)
    * sex chromosome aneuploidy filter
    * White.british.ancestry filter
    * **QCed sample count: 337199 samples** 

### imputed-v3 Variant QC

  * __imputed-v3 parameters__
    * Autosomes and X chromosome (but not pseudo-autosomal region or XY)
    * SNPs from HRC, UK10K, and 1KG imputation (~90 million)
    * INFO score > 0.8
    * MAF > 0.0001
	  * Exception: VEP annotated Missense and PTV MAF > 1e-6
    * HWE p-value > 1e-10  
	* **QCed SNP count: 13.7 million** 
  * __imputed-v2 parameters__
    * Autosomes only
    * SNPs from HRC imputation (~40 million)
    * INFO score > 0.8
    * MAF > 0.0001
	* **QCed SNP count: 10.9 million** 

### imputed-v3 Association model

  * __imputed-v3 model__
    * Linear regression model in Hail (linreg)
    * Three GWAS per phenotype
	    * Both sexes
	    * Female only
	    * Male only
    * Covariates: 1st 20 PCs + sex + age + age^2 + sex*age + sex*age2
    * Sex-specific covariates: 1st 20 PCs + age + age^2 
    * Extra column for variant confidence in case/control phenotypes
      * column name: expected_case_minor_AC
      * Used to filter out false-positive SNPs when case count is low
      * [Blog details here](http://www.nealelab.is/blog/2017/9/11/details-and-considerations-of-the-uk-biobank-gwas)  
  * __imputed-v2 model__
    * Linear regression model in Hail (linreg)
    * Covariates: 1st 10 PCs + sex