Post-GWAS polygenic risk scores (PRS) pipeline

1 - Description

This pipeline calculates polygenic risk scores (PRS) using PRSice. It requires the following inputs:

• A target cohort: genotype data of the individuals for which you wish to obtain PRS scores.

• A target phenotype: a file specifying sample IDs, phenotypes and covariates.

• A base cohort: GWAS summary statistics which will be used to calculate the PRS. These can be either:

  • SAIGE formatted summary statistics (i.e. an output of the lifebit-ai/biobank-gwas pipeline)

  • GWAS catalogue summary statistics (still in development)

For more usage details, including a description of all available parameters, see docs/usage.md

2 - Important assumptions

In its current implementation, the pipeline assumes it is being run post-GWAS, more specifically, after having run the lifebit-ai/biobank-gwas via the CloudOS Cohort Browser. It therefore assumes the following about the target dataset and its correspond phenotype file:

• This PLINK files are the output of the lifebit-ai/biobank-gwas pipeline. These PLINK files have therefore already undergone standard QC.

• In accordance with the previous point, the phenotype file must correspond to the phenotype file used by lifebit-ai/biobank-gwas (run via the CloudOS Cohort Browser). See example in testdata/cohort_parsed_file.phe.

• The target data consists of PLINK files, split by chromosome. See example in testdata/plink.

3 - Example usage (using SAIGE summary statistics as base cohort):

nextflow run main.nf \
--saige_base testdata/saige_results_covid_1.csv \
--target_pheno testdata/cohort_parsed_file.phe \
--target_plink_dir testdata/plink

For more usage details, including a description of all available parameters, see docs/usage.md.