What SNP genotyping errors are most costly for genetic association studies?

Area of Science:

• Genetics
• Statistical genetics
• Bioinformatics

Background:

• Case/control studies are crucial for genetic association research.
• Genotyping errors can impact study power and necessitate larger sample sizes.
• Understanding error costs is vital for efficient study design.

Purpose of the Study:

• To identify the most costly genotype misclassification errors in SNP-based case/control studies.
• To quantify the impact of these errors on sample size necessary (SSN) for maintaining statistical power.
• To provide guidance for optimizing genotyping accuracy in genetic research.

Main Methods:

• Utilized a 2x3 chi-squared test of independence for SNP analysis.
• Employed a linear Taylor series expansion of the noncentrality parameter to approximate SSN.
• Evaluated two scenarios: Hardy-Weinberg equilibrium (HWE) in cases and controls, and HWE in controls only.
• Assessed error impact across varying minor SNP allele frequencies.

Main Results:

• Misclassifying the common homozygote as the less common homozygote incurs the highest cost, particularly as minor allele frequency approaches zero.
• Misclassification of common homozygotes to heterozygotes also shows indefinitely increasing costs with decreasing minor allele frequency.
• Heterozygote to less common homozygote misclassification has a bounded but significant cost.

Conclusions:

• Genotyping errors, especially those involving homozygotes and low minor allele frequencies, substantially inflate sample size requirements.
• Careful attention to genotyping accuracy is essential for SNPs with low minor allele frequencies to achieve desired statistical power.
• Automated genotyping systems should prioritize minimizing error types with high cost coefficients.