TreeQTL: hierarchical error control for eQTL findings

Area of Science:

• Genetics
• Bioinformatics
• Statistical Genomics

Background:

• Expression quantitative trait loci (eQTL) studies are crucial for understanding gene regulation.
• Common multiplicity adjustment methods struggle to control error rates in complex eQTL analyses.
• Accurate error control is vital for reliable identification of genetic associations with gene expression.

Purpose of the Study:

• To introduce TreeQTL, an R package designed for robust multiple testing in eQTL studies.
• To implement a hierarchical multiple testing procedure for improved error rate control.
• To provide a reliable tool for researchers conducting eQTL analyses.

Main Methods:

• Development of the TreeQTL R package.
• Implementation of a hierarchical multiple testing procedure.
• Application of the method to control error rates based on grouped eQTL hypotheses.

Main Results:

• TreeQTL effectively controls error rates where standard methods fail.
• The hierarchical procedure allows for tailored error rate control.
• Provides a more reliable framework for reporting eQTL findings.

Conclusions:

• TreeQTL offers a significant advancement in multiple testing for eQTL studies.
• The hierarchical approach enhances the accuracy and interpretability of eQTL results.
• Researchers can improve the reliability of their findings using TreeQTL.