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RTeQTL: Real-Time Online Engine for Expression Quantitative Trait Loci Analyses.

Baoshan Ma¹, Jinyan Huang², Liming Liang¹

¹College of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning Province, China 116026, Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA 02115 and Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA 02115College of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning Province, China 116026, Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA 02115 and Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA 02115 lliang@hsph.harvard.edu.

Database : the Journal of Biological Databases and Curation

|July 20, 2014

Summary

A new tool, Real-Time Engine for Expression Quantitative Trait Loci Analyses (RTeQTL), offers novel analyses for gene expression and single nucleotide polymorphism (SNP) data. It provides unique insights into eQTL associations, including conditional effects, not found in other databases.

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Area of Science:

Genomics
Bioinformatics
Systems Biology

Background:

Existing expression quantitative trait loci (eQTL) databases have limitations in providing comprehensive association results.
There is a need for tools that can analyze conditional eQTL effects and identify associations for candidate genes.
Current browsers often only store genome-wide significant P-values, missing potentially relevant biological signals.

Purpose of the Study:

To introduce the Real-Time Engine for Expression Quantitative Trait Loci Analyses (RTeQTL) database tool.
To enable efficient computation and browsing of single and two-SNP conditional eQTL effects.
To provide a unique resource for exploring eQTL associations, including those missed by existing browsers.

Main Methods:

Development of the RTeQTL database tool.
Utilizing lymphoblastoid cell line data from over 900 samples.
Incorporating global gene expression and genome-wide genotyped and imputed SNP data.
Implementing functions for single and two-SNP conditional eQTL analyses.

Main Results:

RTeQTL provides eQTL association results not available in existing databases.
The tool efficiently computes and browses detailed results for gene-SNP pairs.
It uniquely assesses the independent effect of SNPs on gene expression, conditioning on other SNPs.
Identifies eQTLs for candidate genes, regardless of P-value magnitude.

Conclusions:

RTeQTL is a valuable tool for comprehensive eQTL analysis.
It enhances the discovery of gene- SNP associations, particularly for candidate genes and conditional effects.
The database facilitates online browsing, batch downloading, and gender stratification for eQTL data.