# HT-eQTL: Integrative Expression Quantitative Trait Loci Analysis in a Large Number of Human Tissues

## TL;DR

This paper introduces HT-eQTL, a scalable hierarchical Bayesian method for multi-tissue eQTL analysis that improves discovery power and computational efficiency across numerous human tissues, exemplified on GTEx data.

## Contribution

The paper presents a novel scalable hierarchical Bayesian framework for multi-tissue eQTL analysis, enabling efficient genome-wide studies across many tissues.

## Key findings

- Outperforms existing methods in computational speed and eQTL discovery power.
- Effectively identifies tissue-specific and shared eQTLs.
- Demonstrated on GTEx data with superior results.

## Abstract

Expression quantitative trait loci (eQTL) analysis identifies genetic markers associated with the expression of a gene. Most existing eQTL analyses and methods investigate association in a single, readily available tissue, such as blood. Joint analysis of eQTL in multiple tissues has the potential to improve, and expand the scope of, single-tissue analyses. Large-scale collaborative efforts such as the Genotype-Tissue Expression (GTEx) program are currently generating high quality data in a large number of tissues. However, computational constraints limit genome-wide multi-tissue eQTL analysis. We develop an integrative method under a hierarchical Bayesian framework for eQTL analysis in a large number of tissues. The model fitting procedure is highly scalable, and the computing time is a polynomial function of the number of tissues. Multi-tissue eQTLs are identified through a local false discovery rate approach, which rigorously controls the false discovery rate. Using simulation and GTEx real data studies, we show that the proposed method has superior performance to existing methods in terms of computing time and the power of eQTL discovery. We provide a scalable method for eQTL analysis in a large number of tissues. The method enables the identification of eQTL with different configurations and facilitates the characterization of tissue specificity.