MACH2QTL

MACH2QTL performs genotype imputation–based QTL analysis to infer unobserved genotypes and increase statistical power in genome-wide association studies (GWAS).

Key Features:

• Genotype Imputation: Implements genotype imputation to infer unobserved genotypes from observed marker data.
• Imputed Dosages and Posterior Probabilities: Uses imputed dosages or posterior genotype probabilities as input for downstream analysis.
• Increased Analytical Power: Enhances detection of trait-associated loci by leveraging imputed genotypes to increase statistical power in QTL analyses.
• Cross-Study Integration: Supports combining results across studies and distinct genotyping platforms to facilitate meta-analyses and integration with whole genome resequencing datasets.

Scientific Applications:

• Gene Mapping Studies: Summarizes and refines gene mapping results by incorporating imputed genotypes to identify loci associated with complex traits.
• GWAS Enhancement: Extends genome-wide association scans by enabling association testing at markers not directly genotyped.

Methodology:

Implements advanced statistical models for genotype imputation and uses imputed dosages or posterior genotype probabilities to perform QTL analysis.