Issues and challenges of imputation techniques in genome wide association studies (GWAS): A review

A genome-wide association study (GWAS) rapidly scans DNA markers in many individuals to find genetic links to diseases. New findings aid in disease detection, treatment and prevention. Imputation predicts untyped genotypes in genetic studies when data is missing due to quality, cost, or design issues. It's a proven statistical technique for estimating unobserved genotypes by borrowing haplotype segments from a densely genotyped reference panel. This allows estimation and testing of associations at unassayed variants. Genotype imputation is vital in analyzing genome-wide association scans, helping geneticists evaluate evidence for association at untyped genetic markers. This summary outlines missing data issues and various imputation methods.