Controlling false positives in the mapping of epistatic QTL

Area of Science:

• Genetics and Genomics
• Statistical Genetics
• Bioinformatics

Background:

• Controlling false positive rates (FPR) in quantitative trait loci (QTL) mapping, particularly for epistasis, remains a challenge.
• Epistasis, the interaction between genes, plays a crucial role in complex trait inheritance but is difficult to detect accurately.

Purpose of the Study:

• To develop and evaluate a novel nested test framework for controlling FPR in pairwise epistatic QTL mapping.
• To compare the performance of one-dimensional and two-dimensional genome scans for detecting epistasis.
• To provide a robust method for high-throughput epistasis analyses.

Main Methods:

• Development of a nested test framework incorporating one-dimensional and two-dimensional genome scans.
• Utilized permutation methods to derive genome-wide thresholds for multiple testing correction.
• Conducted large-scale simulations to assess FPR, power, and accuracy across various epistasis scenarios.

Main Results:

• The nested test framework and genome-wide thresholds effectively controlled FPR at the 5% level.
• The one-dimensional approach showed higher power for detecting QTL-associated epistasis, capturing most pairs found by the two-dimensional approach.
• The two-dimensional approach uniquely identified epistatic QTL with weak main effects; combining both approaches improved detection of diverse epistasis forms.

Conclusions:

• The proposed nested test framework is essential for accurate control of FPR in epistatic QTL mapping.
• Combining one- and two-dimensional scanning strategies offers a comprehensive approach for detecting various forms of epistasis.
• This framework serves as an effective search engine for high-throughput epistasis analyses in genetic studies.