Haplotype sharing analysis with SNPs in candidate genes: the Genetic Analysis Workshop 12 example

Area of Science:

• Genetics
• Statistical Genetics
• Bioinformatics

Background:

• Investigating genetic associations with affection status is crucial for understanding disease.
• Haplotype analysis is a key method for identifying disease-causing variants.
• Simulated data from Genetic Analysis Workshop (GAW) 12 provides a controlled environment for method evaluation.

Purpose of the Study:

• To compare the effectiveness of Haplotype Sharing Statistics (HSS) and Transmission Disequilibrium Test (TDT) in identifying disease-associated single nucleotide polymorphism (SNP) haplotypes.
• To evaluate these methods using simulated data with a known disease-causing variant in candidate gene 1.
• To understand the factors influencing the performance of HSS and TDT.

Main Methods:

• Haplotype estimation using GENEHUNTER.
• Application of Haplotype Sharing Statistics (HSS) test statistic.
• Application of Transmission Disequilibrium Test (TDT) analysis.
• Analysis of simulated data from isolated and general populations.

Main Results:

• HSS provided strong evidence for SNP involvement in the isolated population but did not pinpoint the true variant.
• TDT analysis identified the disease-causing variant in both isolated and general populations, with superior performance in the general population.
• Simulations indicated that closely spaced SNPs in strong linkage disequilibrium and ambiguous haplotypes negatively impact HSS performance.

Conclusions:

• TDT demonstrates superior performance over HSS in pinpointing disease-causing variants within candidate genes, particularly in outbred populations.
• The accuracy of HSS is compromised by complex SNP linkage disequilibrium patterns and haplotype ambiguity.
• These findings highlight the importance of selecting appropriate statistical methods for genetic association studies.