Characterization and correction of error in genome-wide IBD estimation for samples with population structure

Area of Science:

• Population Genetics
• Genomic Analysis
• Statistical Genetics

Background:

• Estimating genome-wide identical by descent (IBD) sharing is crucial for genetic studies.
• Methods like PLINK's moment estimator are widely used for IBD estimation.
• These methods assume a single, homogeneous population, which is often not the case.

Purpose of the Study:

• To evaluate the impact of population structure on IBD estimation using the PLINK method of moments.
• To quantify the bias and inflated variance introduced by population structure.
• To propose a method for improving IBD estimates in the presence of population structure.

Main Methods:

• Utilized simulated pedigrees to model different population structure scenarios.
• Applied the PLINK method of moments estimator to assess IBD sharing.
• Developed and tested a SNP pruning strategy to mitigate bias.

Main Results:

• Demonstrated that population structure inflates variance and biases IBD estimates.
• Observed that the PLINK estimator often overestimates relatedness between ancestrally similar individuals.
• Quantified the performance of the PLINK estimator under various population structure conditions.

Conclusions:

• The assumption of a homogeneous population is critical for accurate IBD estimation.
• Population structure significantly impacts the reliability of standard IBD estimation methods.
• SNP pruning presents a viable approach to enhance the accuracy of genome-wide IBD estimates in admixed or structured populations.