Skip to content

README.md

Latest commit

 

History

History
executable file
·
33 lines (19 loc) · 935 Bytes

README.md

File metadata and controls

executable file
·
33 lines (19 loc) · 935 Bytes

Description

This pipeline runs PoPS analysis for a given set of features. See PoPS GitHub for more information on PoPS analysis.

It performs the following steps:

  1. Annotate genes with MAGMA scores
  2. Run PoPS with gene features
  3. Empirically calculate p-values

Quickstart

Quickstart for deploying this pipeline locally and on a high performance compute cluster.

1. Set up the environment

Create conda environment: envs/environment.yml and activate:

conda activate snakemake_pps

Alternatively, if using singularity or docker, one can pull the image from henryjt/snakemake-polygenic_priority_score:latest.

2. Prepare the input files

See demo/data/features for example input files. See docs/README-params.md for description of parameters.

3. Run pipeline

See demo/run_pops__local_docker.sh for example of how to run full pipeline

Author: Henry Taylor