Use of weighted p-values in regional inference procedures

Area of Science:

• Genetics
• Statistical genetics
• Bioinformatics

Background:

• Previous research indicated moving averages of p-values enhance linkage detection power compared to single p-value tests.
• Statistical methods are crucial for identifying genes underlying quantitative traits in genetic studies.

Purpose of the Study:

• To evaluate if weighting middle p-values in a sequence further improves linkage detection power.
• To compare weighted moving average tests with multipoint linkage tests for gene identification.

Main Methods:

• Simulated extended pedigree data from the general population was analyzed.
• Variance components method implemented in GENEHUNTER was used for linkage analysis.
• 14-marker regions on chromosomes 19 and 1 were tested for linkage to quantitative traits Q1 and Q5.

Main Results:

• The moving average test demonstrated greater power than single p-value tests, consistent with prior findings.
• A weighting procedure occasionally increased power, achieving results comparable to multipoint analysis, but not consistently.
• All tested methods exhibited low power, preventing definitive conclusions about the superiority of specific weighting schemes.

Conclusions:

• Weighted moving average methods show potential for improving linkage detection but require further investigation.
• The study highlights the challenges in gene linkage analysis with complex traits and limited statistical power.
• Further research is needed to optimize weighting strategies for robust gene identification in genetic studies.