Performing QTL and eQTL Analyses with the R-Package GenomicTools.

Area of Science:

• Genomics
• Bioinformatics
• Statistical Genetics

Background:

• Quantitative trait locus (QTL) and expression QTL (eQTL) analyses are crucial for understanding genotype-phenotype relationships.
• Existing methods for QTL/eQTL analysis can be complex and sensitive to data outliers.
• A user-friendly R package can facilitate wider adoption and application of these analyses.

Purpose of the Study:

• To introduce the R-package GenomicTools for user-friendly QTL and eQTL analyses.
• To explain the theoretical underpinnings of the implemented statistical methods.
• To provide practical guidance on using the package for data analysis and visualization.

Main Methods:

• Implementation of a standard linear model approach for QTL/eQTL testing.
• Development of a novel non-parametrical directional testing method robust to outliers.
• Detailed documentation including package installation, data import, analysis execution, and figure generation.

Main Results:

• The GenomicTools package provides a comprehensive and accessible platform for performing QTL and eQTL analyses.
• The directional testing method offers an alternative to standard approaches, enhancing robustness.
• The package includes functionalities for creating publication-ready figures.

Conclusions:

• GenomicTools simplifies complex genomic analyses, making QTL and eQTL studies more accessible.
• The package's features support researchers in generating robust and visually appealing results.
• It contributes to the broader analysis of genomic data, aiding in the discovery of genetic associations.