fastENLOC: fast enrichment estimation aided colocalization analysis

This repository contains the software implementation of fastENLOC, which enables integrative genetic association analysis of molecular QTL data and GWAS data. The statistical model and the key computational procedures are described in [1] and [2]. Compared to the previous implementation of ENLOC, the new implementation is a standalone C++ program and runs magnitude faster.

For questions/comments regarding to the software package, please contact Xiaoquan (William) Wen (xwen at umich dot edu).


Software distributed under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. See LICENSE for more details.

Tutorial and guideline

A detailed tutorial is provided in tutorial directory. Briefly, three main steps are required for a complete analysis

  1. Prepare eQTL annotation
  2. Prepare GWAS sumary (in term of posterior inclusion probabilities, or PIPs)
  3. Run fastenloc

We distribute pre-computed eQTL annotations from GTEx (v8) data. In the simplest case, the required GWAS PIPs can be computed from single-SNP association summary-statistics (e.g., z-scores and p-values) using torus

GTEx v8 multi-tissue eQTL annotations for fastENLOC

If you prefer to using newly released GTEx v8 eQTL annotation for analysis, please download the following vcf files


  1. Wen, X., Pique-Regi, R., Luca, F. Integrating Molecular QTL Data into Genome-wide Genetic Association Analysis: Probabilistic Assessment of Enrichment and Colocalization. PLOS Genetics. 2017 Mar 13(3): e1006646.
  2. Pividori and Rajagopal et al. PhenomeXcan: Mapping the genome to the phenome through the transcriptome. BioRxiv 2019: doi: 10.1101/833210


Colocalization analysis of genetic association signals

Fastenloc Info

⭐ Stars 15
🔗 Source Code
🕒 Last Update a year ago
🕒 Created 2 years ago
🐞 Open Issues 1
➗ Star-Issue Ratio 15
😎 Author xqwen