imputeqc

imputeqc evaluates genotype imputation quality and optimizes imputation model parameters for imputations produced by fastPHASE and BEAGLE to support downstream analyses such as genome-wide association studies (GWAS).

Key Features:

• Imputation Quality Assessment: Assesses accuracy of genotype imputations using masked data analysis and discordance metrics between imputed genotypes.
• Parameter Optimization: Optimizes model parameters including the number of haplotype clusters and expectation-maximization cycles for fastPHASE and related methods.
• Compatibility with Various Formats: Accepts outputs from fastPHASE (version 1.4.8) and BEAGLE and handles compatible input files such as *.inp and VCF formats.
• Masked Data Analysis: Implements masked data analysis to evaluate imputation quality without bias from known genotypes.
• Efficiency in Computational Resources: Reduces computational time for downstream analyses such as hapFLK testing (example reported: from three days to ~20 hours) by optimizing imputation parameters.

Scientific Applications:

• Genome-Wide Association Studies (GWAS): Improves power and reliability of GWAS by enhancing imputation accuracy for downstream association testing.
• Haplotype Analysis: Supports haplotype-based analyses including hapFLK testing and detection of selection signatures, exemplified by detection at the LCT region on chromosome 2.

Methodology:

imputeqc applies masked data analysis, computes discordance metrics between imputed genotypes from fastPHASE and BEAGLE to assess accuracy, and tunes the number of haplotype clusters and expectation-maximization cycles.