How to run finemapping pipeline

Pipelines for finemapping of GWAS results using FINEMAP and SuSiE.

Introduction

By finemapping, we mean identifying the variants with the highest probability of being causal from your GWAS summary statistics. In the Sandbox, we have a pipeline for doing this using summary statistics. The pipeline calculates linkage disequilibrium (LD) between variants in the locus using LDstore2 and then using LD matrices and summary statistics finemaps each genome-wide significant (P<5E-8) locus in the supplied summary statistics using a combination of FINEMAP and SuSiE. A detailed description of the pipeline can be found from the Github repository.

Alternatively, users can provide their own custom regions to finemap instead of the automatic selection for regions with genome-wide significant variants.

Running finemapping in sandbox

There are multiple ways to run the finemapping pipeline with your custom GWAS results but we strongly recommend the unmodifiable finemapping pipeline (see below).

Unmodifiable finemapping pipeline (R12 and later)

With the introduction of unmodifiable pipelines, the easiest and most recommended way to get your custom GWAS endpoint finemapped is with the unmodifiable finemapping pipeline. Using this pipeline will mean that your results are automatically uploaded to the userresults Pheweb and automatically transferred to the green library so that no download request is needed.

Modifiable finemapping pipeline (R12 and earlier)

We recommend the unmodifiable finemapping pipeline to run custom GWAS finemapping, which will suit most users' needs. However, we still provide access to the finemapping scripts (see Modifiable Finemapping pipeline), which may be useful for earlier (pre-R12) releases or if you wish to further customise the finemapping options.

Additional information

• For information on the contents and format of the finemapping pipeline output files, please see Finemapping results format.

• For a demonstration on how to run Finemapping, please watch the presentation given by Bridget Riley-Gillis in the February 8th 2022 FinnGen Users' meeting. Link to recording