Scaling Walled Gardens: the power of meta-analysis on summary statistics data

Garay post

Chris Garay, Ph.D., Director, Paradigm4 Life Science Applications

Imagine having easy access and meta-analysis for public genetic association summary statistics together with your expanding collection of proprietary association datasets. Each dataset provides a unique window into the role human genetic variation plays in disease. While datasets are valuable on their own, their true potential can be unlocked when they are intelligently integrated to reveal patterns that remain hidden with individual analyses.

genetic association

Meta-analysis amplifies your statistical power, helping to detect robust genetic associations with rare variants and to reveal population-specific genetic effects.

deCODE UK Biobank FinnGen Our Future Health
All of US Million Veterans Program Biobank Japan China Kadoorie
AGD Precise Singapore Discover Me South Africa Galatea
Ovation Helix IBD Plexus Truveta

The catch? Each dataset is captive within a “walled garden”, hosted in its own SaaS cloud environment that may or may not have the functionality and performance you need. Scientists struggle with these persistent challenges:

  1. Getting access to multiple, disconnected platforms
  2. Navigating multiple vendors’ analytical environments, which may involve uploading analytical or annotation packages the scientist is accustomed to using
  3. Harmonizing phenotype definitions and dealing with allele flipping
  4. Exporting derived results for downstream analysis (including meta-analysis) while maintaining data provenance

Paradigm4’s solution combines export services with a unified biomedical analytics platform optimized specifically for large summary stats datasets and cross-dataset analysis.

  1. Our Customers Solutions team—with experience working in these walled gardens—can set up and execute data queries, variant annotation pipelines, and summary stats data analyses.
  2. Our REVEAL platform serves as a central hub for accessing data and synthesizing knowledge across diverse datasets
  3. The Meta-analysis application comes with: 
    • Preloaded with summary statistics data from organizations like the Broad Institute, deCODE, and FinnGen
    • Data connectors and pre-processing pipelines for pulling data from walled gardens into REVEAL
    • Ready-to-run Jupyter notebooks featuring meta-analysis tools like METAL and remeta, plus essential tools like PRS, MR, PWCoCo, Cojo
  4. P4’s DataTrail tracks provenance and the workflows used to generate derived results

Plus, REVEAL is highly optimized for sub-second, constant-time interactive performance even as the number of association datasets grow.

 Can P4 help you REVEAL more powerful evidence for your research questions?

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