Estimating genotyping error rates from Mendelian errors in SNP array genotypes and their impact on inference.

Area of Science:

• Genetics
• Bioinformatics
• Statistical genomics

Background:

• High-throughput genotyping methods like SNP arrays are crucial for genetic research.
• Accurate estimation of genotyping error rates is essential for reliable downstream analyses.
• Mendelian errors provide a valuable resource for inferring genotyping accuracy.

Purpose of the Study:

• To describe a simple method for inferring genotyping error rates from Mendelian errors.
• To apply this method to SNP array data and assess the error rate.
• To evaluate the impact of genotyping errors on linkage inference in family studies.

Main Methods:

• Utilized Mendelian errors within small families to infer genotyping error rates.
• Applied the method to genotype data from the Affymetrix GeneChip Human Mapping 50 k Array.
• Employed simulated data to assess the impact of error rates on linkage analysis.

Main Results:

• The genotyping error rate was estimated to be approximately 0.1% for the SNP array.
• Increasing the quality criterion for genotype calls reduced the error rate but also decreased the call rate.
• Simulated data indicated that the observed error rate had minimal impact on identity-by-descent-based linkage inference in sib-pair studies.

Conclusions:

• A straightforward method for estimating genotyping error rates from Mendelian inconsistencies is presented.
• The Affymetrix 50 k SNP array exhibits a low genotyping error rate, suitable for family-based genetic studies.
• The findings suggest that current SNP array technology provides sufficient accuracy for robust linkage analysis in sib-pair studies.