sim1000G

sim1000G simulates genetic variant and pedigree data in R from phased VCF input to produce genotype datasets that preserve haplotype structure and linkage disequilibrium (LD) for evaluation of genetic association and family-based analyses.

Key Features:

• Implementation and input: Implements simulations in R and accepts raw phased Variant Call Format (VCF) files as input.
• Haplotype extraction and LD computation: Extracts haplotypes from phased VCF to compute linkage disequilibrium (LD) in simulated genomic regions.
• Genotype generation for unrelated individuals: Generates genotype data by modeling covariance across variants to capture allele frequency diversity and short- and long-range LD.
• Family-based simulation and recombination: Models recombination events to simulate pedigrees of arbitrary sizes, including three-generation pedigrees.
• Population scenarios: Simulates unrelated individuals from a single population or two distinct populations and captures subtle population differences in LD structure.
• Parameter-free simulation: Operates without tuning parameters to generate variant data.

Scientific Applications:

• Evaluation of statistical methods: Generates realistic genotype and pedigree data to benchmark statistical and computational methods in human and animal genetics.
• Association studies of rare and common variants: Simulates data for testing association methods for both rare and common variants.
• Family-based study development: Enables development and validation of methods for linkage and family-based association analyses using simulated pedigrees.
• Population genetics and LD analysis: Supports investigations of LD structure and population-specific genetic patterns.

Methodology:

The software extracts haplotypes from phased VCF files, computes linkage disequilibrium (LD) in target regions, uses covariance across variants to generate genotype data that preserves allele frequencies and short- and long-range LD, and models recombination events to construct pedigrees of varying sizes.