Testing for Hardy-Weinberg equilibrium in structured populations using genotype or low-depth next generation...

Area of Science:

• Population Genetics
• Bioinformatics
• Genomic Data Analysis

Background:

• Hardy-Weinberg equilibrium (HWE) testing is crucial for genetic quality control.
• Next-generation sequencing (NGS) enables large-scale studies but introduces statistical uncertainty.
• Population structure in diverse ancestries can confound HWE testing.

Purpose of the Study:

• To develop a method for testing HWE that accounts for population structure.
• To enable detection of HWE deviations caused by factors other than population structure.
• To improve the reliability of genetic quality control in large-scale NGS studies.

Main Methods:

• Proposed a novel statistical method incorporating population structure into HWE testing.
• Utilized principal component analysis (PCA) for population structure inference.
• Employed genotype likelihoods to model uncertainty in low-depth NGS data.

Main Results:

• Demonstrated the effectiveness of the proposed method (PCAngsd) on simulated and real datasets.
• Showcased successful application in low-depth NGS and genotype data.
• Validated the ability to detect HWE deviations beyond population structure effects.

Conclusions:

• The developed method accurately tests for HWE while controlling for population structure.
• This approach enhances the identification of technical errors or evolutionary signals in genetic data.
• PCAngsd provides a robust tool for analyzing large-scale, diverse NGS datasets.