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gibran hemani edited this page Oct 20, 2024 · 32 revisions

Background

Welcome to the Lifecourse-GWAS wiki!

This wiki will guide you through the Lifecourse-GWAS consortium analysis. Here, you will be able to find instructions for data preparation and access code to generate genome-wide association studies (GWASs) on time-varying phenotypes. We are collecting data on a comprehensive list of phenotypes every year up until 18 years of age and every five years after 18 years of age.

We have prepared the pipeline to minimise time and energy required by analysts to contribute data to the overall effort, ensure harmonisation across cohorts, and minimise errors. The use of standardised procedures across all samples is critical in order to increase the effectiveness of the subsequent meta-analyses that we be run internally upon receipt of these GWAS. Because there is always a chance of error, we may ask some analyses to be re-run. We encourage analysts to organize and save their scripts, files, and directories just in case a re-analysis is required.

This pipeline forms part of the overall Analysis plan. Specifically, it implements the per-cohort age-stratified GWAS studies that will contribute to an overall age-stratified meta analysis.

LifecourseGWAS-cohort-pipeline drawio-2

Principles of collaboration

Please read the Principles of Collaboration here which details information about software and data sharing, publication and authorship, and extensions to the work.

Sign up

If you have a cohort that could make a contribution to these analyses please use the sign up form to register.

Contact details

Questions about this Wiki or running the pipeline can be directed to: lifecourse-gwas-group@bristol.ac.uk

The working group for this consortium consists of:

  • Grace M. Power
  • Genevieve Leyden
  • David Carslake
  • Eleanor Sanderson
  • Gibran Hemani

Lifecourse GWAS consortium website: https://lifecourse-gwas.github.io

Bug reports

Please use the Github Issues page to describe any technical issues you encounter with running the pipeline.

Credits

This pipeline uses a number of important pieces of software