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Kipoi-GWAS
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README.md
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Kipoi-GWAS
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 # `Kipoi-GWAS` Kipoi-GWAS is a snakemake pipeline which - downloads UK BioBank association files - merges the annotation files with variant effect predictions using Kipoi - runs FGWAS to fine-map variants - generates a report A sample report can be found here: [src/fgwas_plot.ipynb](src/fgwas_plot.ipynb). ## General workflow of Kipoi-GWAS  ## Installation 1. Clone the git repo. ``` git clone https://github.com/NCBI-Hackathons/Kipoi-GWAS ``` 2. Install conda environment. ``` conda env create -f environment.yml ``` 3. Install the python package ``` cd Kipoi-GWAS; pip install . ``` ## Folder structure Here is the complete folder structure. ``` input/ UKBB/ # UK-biobank phenotypes downloaded from the UK Biobank site. Select phenotypes of interest. TODO {phenotype}.gwas.imputed_v3.both_sexes.tsv.bgz {phenotype}.gwas.imputed_v3.both_sexes.tsv # after untarring the .bgz file anno/ # variant annotation of the phenotypes found in UKBB kipoi/ # annotated variants using `kipoi veff score_variants` subset/ {chr}/ {model}.tsv.gz output/ {phenotype}/ subset/ {chr}/ {run-id}/ metadata.json # information about the run fgwas/ input/ # input tables for fgwas output/ # output of fgwas, includes default outputs report/ # reports fig1.ipynb fig1.html ``` ### Placeholders - `{phenotype}` - the UKBB phenotype code goes here - `{chr}` - results are generated for associations in a particular chromosome. Example: chr12 - `{run-id}`- this is a manually selected placeholder which allows for the pipeline to be run for different combinations of variant annotations
