GWAS Analysis

Module Overview

The GWAS Analysis module enables Genome-Wide Association Studies to identify genetic variants associated with phenotypes, diseases, or quantitative traits across cohorts.

What This Module Does

Genome-Wide Association Studies (GWAS) are a cornerstone of modern genomics, linking genetic variation to observable traits.

CompuBio’s GWAS module provides a reproducible, scalable, and interpretable framework for performing association studies across large cohorts.

It helps answer questions such as:

Which variants are associated with a disease or trait?
How strong and reliable are these associations?
Are results confounded by population structure?

Supported Study Designs

The GWAS module supports multiple experimental designs:

Case / Control Studies
- Disease vs healthy cohorts
- Binary phenotype association testing
Quantitative Trait Analysis
- Continuous phenotypes (e.g. expression, measurements)
- Linear or mixed models

Study Design Matters

Clear phenotype definitions and balanced cohorts significantly improve statistical power and interpretability.

Statistical & Population Controls

To ensure robust and reliable association results, CompuBio includes built-in correction mechanisms.

Population Stratification Correction
- Principal component analysis (PCA)
- Covariate inclusion in association models
Multiple Testing Control
- Genome-wide significance thresholds
- Adjusted p-values

Confounding Risk

Failure to account for population structure can lead to spurious associations. Always inspect PCA and QQ plots.

Outputs & Visualizations

GWAS results are presented through publication-ready visualizations and exportable data tables.

Plots

Manhattan plots for genome-wide significance
QQ plots for inflation and model diagnostics

Tables

Variant-level association statistics
Effect sizes and confidence intervals
Annotated variant summaries

All outputs can be downloaded or further explored inside interactive dashboards.

Variant Annotation Integration

GWAS results are seamlessly integrated with variant annotation pipelines.

Functional consequence annotation
Gene-level context
Linking significant variants to downstream interpretation

From Association to Insight

Association signals can be directly connected to variant annotation and AI interpretation modules for deeper biological understanding.

Plan Availability

The GWAS Analysis module is available on the following plans:

Pro: Full GWAS workflows and visualization
Team: Collaboration, shared workspaces, and automation

Plan Gating

Starter plans include core genomics and microbiome workflows, while advanced association studies are enabled on Pro and Team plans.

Best Practices

Use high-quality genotype and phenotype data
Ensure consistent reference builds across datasets
Inspect QC, PCA, and QQ plots before interpretation
Combine GWAS results with biological annotation for context

What’s Next?

Variant annotation and prioritization
AI-driven disease association analysis
Integrating GWAS with multi-omics data