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seeQTL: a searchable database for human eQTLs.

Kai Xia¹, Andrey A Shabalin, Shunping Huang

¹Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. kxia@bios.unc.edu

Bioinformatics (Oxford, England)

|December 16, 2011

Summary

This summary is machine-generated.

seeQTL is a new database integrating expression quantitative trait locus (eQTL) studies. It offers a user-friendly browser for visualizing eQTL association results, aiding genetic research.

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Area of Science:

Genomics
Bioinformatics
Systems Biology

Background:

Expression quantitative trait loci (eQTLs) link genetic variations to gene expression levels.
Integrating diverse eQTL studies is crucial for a comprehensive understanding of gene regulation.
Existing resources may lack a unified platform for accessing and visualizing eQTL data.

Purpose of the Study:

To develop and present seeQTL, a comprehensive database for eQTL information.
To provide a versatile tool for exploring eQTL association results.
To facilitate the meta-analysis of existing eQTL data.

Main Methods:

Compilation of various eQTL studies.
Meta-analysis of HapMap eQTL information.
Development of a web-based browser for data visualization.

Main Results:

seeQTL integrates data from multiple eQTL studies.
The database includes a meta-analysis of HapMap eQTL data.
Results are presented using local-association and genome-wide Manhattan plots.

Conclusions:

seeQTL is a comprehensive and versatile eQTL database.
The browser provides convenient visualization of eQTL association results.
This resource supports genetic research by consolidating and presenting eQTL information.