SQTL

SQTL maps quantitative trait loci (QTLs) influencing human gene expression using a semiparametric, rank-based approach for robust eQTL analysis of high-throughput microarray data.

Key Features:

• Rank-Based Approach: Employs a semiparametric rank-based strategy to analyze expression phenotypes.
• Robustness to Non-Normality: Does not assume a specific distribution for expression phenotypes, mitigating inflated type I error rates and loss of power due to non-normal data or outliers.
• Multiple Testing Adjustment: Incorporates an efficient Monte Carlo procedure to control false positives and assess genome-wide significance across thousands to hundreds of thousands of marker loci.
• High-Throughput Microarray Application: Applied to microarray gene expression datasets, including data from Genetic Analysis Workshop 15, and designed to handle simultaneous measurement of thousands of genes.

Scientific Applications:

• eQTL Mapping: Identification of loci that influence gene expression levels in human studies.
• Genetic Basis of Traits and Diseases: Linking expression-influencing loci to the genetic architecture of complex traits and diseases.
• Robust Analysis of Diverse Datasets: Analysis of datasets with non-normal expression distributions or outliers where traditional parametric methods may fail.

Methodology:

Uses a semiparametric rank-based analysis of expression phenotypes combined with an efficient Monte Carlo procedure for multiple-testing correction without assuming a specific phenotype distribution.