HT-eQTL: integrative expression quantitative trait loci analysis in a large number of human tissues.
BMC Bioinformatics
; 19(1): 95, 2018 03 09.
Article
in En
| MEDLINE
| ID: mdl-29523079
ABSTRACT
BACKGROUND:
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.RESULTS:
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.CONCLUSIONS:
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.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Organ Specificity
/
Gene Expression Regulation
/
Quantitative Trait Loci
Type of study:
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
BMC Bioinformatics
Journal subject:
INFORMATICA MEDICA
Year:
2018
Type:
Article
Affiliation country:
United States