Skip to content
Go to file

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

IMPORTANT: This repository is no longer maintained. In addition to running a TAD_Pathways analysis for Bone Mineral Density GWAS, this analysis pipeline downloads genomic data and explores distributions across TADs. A more streamlined analysis pipeline that does not require data preprocessing is available at

NOTE: Several files built from this pipeline are used in the above repository including the TAD based gene index and the hg19 converted NHGRI-EBI GWAS Catalog.

Incorporating TADs into GWAS Analysis - TAD_Pathways

Gregory P. Way and Casey S. Greene 2016



The repository contains methods for manipulating, observing, and visualizing topologically associating domains (TADs) in the context of SNPs, genes, and repeat elements for human (hg19) and mouse (mm9) genomes.

The repository also proposes methods and tools for the incorporation of TAD domains into the prioritization of GWAS signals through the investigation of publicly available GWAS data. We introduce TAD pathways as a method to identify the likely causal genes from GWAS independent of distance to sentinel SNP.

A preprint of our method is available here on bioRxiv


For all questions and bug reporting please file a GitHub issue

For all other questions contact Casey Greene at or Struan Grant at


There are two ways to implement a TAD_Pathways analysis:

  1. Disease/Trait Specific - Uses GWAS identified SNPs
  2. Custom - Uses custom SNP list

Disease/Trait Specific

Curates the GWAS catalog and TAD boundaries to visualize TADs and generate TAD based gene lists. This will also perform a TAD pathways analysis for Bone Mineral Density GWAS. This will reproduce the analysis and figures used in the paper.

# Using python dependencies
conda env create --quiet --force --file environment.yml
source activate tad_pathways

bash scripts/

This will download data, perform analyses, and output several genomic figures. The command will also output TAD based genes for 299 different GWAS traits. Our TAD_Pathways method can be applied directly using these gene lists.


TAD_Pathways is customizable and allows a user to prespecify any SNP list of interest to test TAD based pathway associations. To perform a custom analysis create a comma separated file where the first row of each column names the list of snps below in subsequent rows.

E.g.: custom_example.csv

Group 1 Group 2
rs12345 rs67891
rs19876 rs54321

Then, perform the following steps:

# Extract locations for SNP list
Rscript --vanilla scripts/tad_util/build_snp_list.R \
        --snp_file "custom_example.csv" \
        --output_file "mapped_results.tsv"

# Build TAD based genelists for each group
python scripts/ \
       --snp_data_file "mapped_results.tsv" \
       --output_file "custom_tad_genelist.tsv"

# The output file is then ready for the manual "TAD_Pathways" steps below


As a case study to demonstrate the utility of a TAD based approach, input the TAD based gene list for the Bone Mineral Density (1,297 genes) into a pathway analysis:

Next, run a WebGestalt pathway analysis on the gene list.

WebGestalt Parameters

Parameter Input
Select gene ID type hsapiens__gene_symbol
Enrichment Analysis GO Analysis
GO Slim Classification Yes
Reference Set hsapiens__genome
Statistical Method Hypergeometric
Multiple Test Adjustment BH
Significance Level Top10
Minimum Number of Genes for a Category 4

Note - The output of scripts/ in data/TAD_based_genes/ for all traits is ready for TAD Pathway Analysis.

After performing the WebGestalt analysis, click Export TSV Only and save the file in data/gestalt/<TRAIT>_gestalt.tsv where <TRAIT> is "BMD" for the example.

GWAS/eQTL Integration

Data Access

Nearest BMD gene GWAS reports

eQTL Browser Parameters

  • Analysis ID (All)
  • Association Test Significance Filters (p-value 1 x 10^-1)
  • Phenotype Traits (Bone Mineral Density)


All analyses were performed in the Anaconda python distribution (3.5.1). For specific package versions please refer to environment.yml. R version 3.3.0 was used for visualization. For more specific environment dependencies refer to our accompanying docker file at docker/Dockerfile


DEPRECATED: Integrating topologically associating domains (TADs) to prioritize GWAS signal





No packages published
You can’t perform that action at this time.