# genal: A Python Toolkit for Genetic Risk Scoring and Mendelian Randomization

Author:

  Cyprien Rivier

Date:

  Mar 25, 2024

Version:

  “0.5”

Genal is a python module designed to make it easy to run genetic risk scores and mendelian randomization analyses. It integrates a collection of tools that facilitate the cleaning of single nucleotide polymorphism data (usually derived from Genome-Wide Association Studies) and enable the execution of key clinical population genetic workflows. The functionalities provided by genal include clumping, lifting, association testing, polygenic risk scoring, and Mendelian randomization analyses, all within a single Python module.

The module prioritizes user-friendliness and intuitive operation, aiming to reduce the complexity of data analysis for researchers. Despite its focus on simplicity, Genal does not sacrifice the depth of customization or the precision of analysis. Researchers can expect to maintain analytical rigour while benefiting from the streamlined experience.

Genal draws on concepts from well-established R packages such as TwoSampleMR, MR-Presso, MendelianRandomization, and gwasvcf, adapting their proven methodologies to the Python environment. This approach ensures that users have access to tried and tested techniques with the versatility of Python’s data science tools.

To install the latest release, type:

    pip install genal

## Contents

- Introduction
- Installation
- Tutorial
  - Data loading
  - Data preprocessing
  - Clumping
  - Polygenic Risk Scoring
  - Mendelian Randomization
  - SNP-association testing
  - Lifting
- The Geno class
  - `Geno`
- Clumping function
  - `clump_data()`
- Extract and PRS functions
  - `extract_snps_func()`

# Indices and tables

- Index

- Module Index

- Search Page

## References

[Hemani.2018]

The MR-Base platform supports systematic causal inference across the human phenome. Hemani G, Zheng J, Elsworth B, Wade KH, Baird D, Haberland V, Laurin C, Burgess S, Bowden J, Langdon R, Tan VY, Yarmolinsky J, Shihab HA, Timpson NJ, Evans DM, Relton C, Martin RM, Davey Smith G, Gaunt TR, Haycock PC, The MR-Base Collaboration eLife. 2018 May 30:7:e34408 34408. PMID: 29846171.

[Verbanck.2018]

Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Marie Verbanck, Chia-Yen Chen, Benjamin Neale, Ron Do. Nature Genetics 2018 May 50(5):693-698 s41588-018-0099-7. PMID: 29686387.

[Lyon.2020]

The variant call format provides efficient and robust storage of GWAS summary statistics. Matthew Lyon, Shea J Andrews, Ben Elsworth, Tom R Gaunt, Gibran Hemani, Edoardo Marcora. bioRxiv 2020 May 30 2020.05.29.115824v1. PMID: 33441155.