mixIndependR

mixIndependR assesses mutual independence of mixed multi-locus genotype panels by testing for non-random associations across loci to inform population genetics and disease studies.

Key Features:

• Mutual Independence Testing: Assesses mutual independence, defined as absence of non-random associations across all subsets of a tested panel, rather than only pairwise linkage disequilibrium (LD).
• Compatibility with Diverse Markers: Supports mixed genetic markers including single nucleotide polymorphisms (SNPs), short tandem repeats (STRs), and insertions and deletions (indels).
• Calculation of Genetic Parameters: Computes allele frequency, genotype frequency, heterozygosity, and tests for Hardy–Weinberg equilibrium from population data.
• Novel Dependence Assessment: Evaluates dependence by comparing observed distributions of summary statistics (e.g., number of heterozygous loci [K] and number of shared alleles [X]) against their expected distributions under mutual independence.
• Higher Analytical Power: Provides increased power relative to traditional pairwise disequilibrium tests for detecting complex genetic interactions in panels with many markers.

Scientific Applications:

• Population Genetics: Analyzes multilocus independence to inform admixture, natural selection, genetic drift, and population demographic inference.
• Disease Studies: Aids selection and combination of variant panels for disease-association studies and strategies addressing multimorbidity.
• Genetic Technology Advancements: Offers a more powerful approach for detecting linkage disequilibrium applicable to real-world genetic data analysis.

Methodology:

Performs functional analysis of mixed genetic panels by computing summary statistics (e.g., K and X) and comparing their observed distributions to expected distributions under mutual independence to identify non-random associations.