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COLocalization of summary STATisticS

Step 1: Select Trait 1 Step 2: Select Trait 2 Step 3: Run Colocalization

1 Select Trait 1

Search and pick the first trait from the database.

Trait

ⓘ Click on a row in the table below to select your trait

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2 Select Trait 2

Pick the second trait to compare with Trait 1.

Trait

ⓘ Click on a row in the table below to select your trait

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3 Run Colocalization

Define region and priors, then run the analysis.

Select genomic region

Manual entry By gene

Choose manual coordinates or select a gene to auto-center the region.

Genomic Region chr:start-end

Maximum span allowed is 5Mb.

Gene selection

Use zoom to refine the flanking region.

Prior H1

Prior H2

Prior H12

Selection Overview

Selected Traits

Selected Genomic Region

Colocalization Summary

Colocalization Plot

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Download Results

Full Report PDF Summary Table CSV Plot PNG Plot PDF

Files will be generated with current selections. Sizes appear after first generation.

Recent Analyses

Quick Start

Get started with COLSTATS in seconds

Try COLSTATS with Example Data

Example Analysis: Rheumatoid Arthritis & CD40 eQTL

We provide a ready-to-use example from our paper demonstrating colocalization between rheumatoid arthritis GWAS and CD40 gene expression.

How to load the example:

Step 1: Go to Step 1 and click "Load sample data Trait 1" to load Rheumatoid Arthritis
Step 2: Proceed to Step 2 and click "Load sample data Trait 2" to load CD40 eQTL
Step 3: Go to Step 3 and click "Load sample data parameters" to set the genomic region (CD40 gene) and default priors

After loading: Click 'Run Colocalization' to see the results

Expected result: PP.H4 = 0.988 (strong colocalization)

What the Example Shows

This example demonstrates colocalization between:

Trait 1: Rheumatoid Arthritis GWAS (GCST000679 from GWAS Catalog)
Trait 2: CD40 gene expression in leukocytes (eQTL from Pala et al. 2017)
Region: chr20:46000000-46200000 (CD40 locus)
Result: PP.H4 = 0.988 (strong evidence for shared causal variant)

Run Your Own Analysis

After trying the example, follow these steps for your own analysis:

Step 1: Select Trait 1

Type keywords to search (e.g., 'rheumatoid', 'BMI', 'blood protein')
Browse the filtered table
Click a row to select your first trait
Click 'Next Step' to proceed

Step 2: Select Trait 2

Search for your second trait or eQTL
Select from the table
Click 'Next Step' to configure analysis

Step 3: Define Region & Run

Choose your genomic region:

Manual entry: Format chr:start-end (e.g., 1:10000-20000, max 5Mb)
By gene: Type gene name to auto-center region ±500kb around TSS

Adjust priors (optional):

Default values work for most cases
H1, H2: prior probability of association for each trait alone
H12: prior probability of shared causal variant

Run the analysis:

Click 'Run Colocalization'
Results appear in seconds

Interpreting Results

Focus on the posterior probabilities (PP):

PP.H4 > 0.8: Strong evidence for colocalization (shared causal variant)
PP.H4 = 0.5-0.8: Moderate evidence
PP.H4 < 0.5: Weak or no evidence for colocalization
Effect directions: Check if top variants show concordant effects across traits

For detailed explanations and troubleshooting, see Help & FAQ

Help & FAQ

Frequently asked questions and troubleshooting

Frequently Asked Questions

What is colocalization analysis?

Colocalization analysis tests whether two traits share the same causal variant in a genomic region. It's commonly used to identify shared genetic architecture between traits or to prioritize functional variants from GWAS studies.

What input data does COLSTATS use?

COLSTATS uses GWAS summary statistics in VCF format from a curated database. The database includes more than 1.6M of publicly available GWAS studies covering various traits and diseases.

What do the posterior probabilities mean?

H0: Neither trait has a genetic association in the region
H1: Only trait 1 has a genetic association
H2: Only trait 2 has a genetic association
H3: Both traits are associated but with different causal variants
H4: Both traits share the same causal variant (colocalization)

How do I interpret PP.H4?

PP.H4 > 0.8: Strong evidence for colocalization
PP.H4 = 0.5-0.8: Moderate evidence
PP.H4 < 0.5: Weak or no evidence for colocalization

What should I do if I get no results?

Common issues and solutions:

Check that both traits have GWAS data in your selected region
Try expanding your genomic region (but keep it under 5Mb)
Verify the chromosome and position format (chr:start-end)
Ensure you selected traits with available VCF files

I found a bug or have a suggestion

We welcome your feedback! Please contact us at:

Email: mauro.pala@irgb.cnr.it

Sources

Summary statistics sources included in COLSTATS

Database Sources

COLSTATS integrates harmonized summary statistics from the following sources. All datasets are aligned to hg38 and formatted as indexed VCF files for fast access.

Total summary statistics available:

Note: Counts represent the number of trait-level summary statistics catalogued in the COLSTATS metadata database. The total is updated automatically when new datasets are added to the collection.