GARLIC

GARLIC infers runs of homozygosity (ROH) from genome-wide SNP datasets to detect autozygosity resulting from identical-by-descent haplotypes and to assist mapping of recessive loci and inference of population history.

Key Features:

• Model-based methodology: Implements the model-based approach of Pemberton et al., 2012 to infer ROH from genome-wide SNP data.
• Population-specific parameters: Incorporates population-specific parameters to tailor ROH inference to different demographic contexts.
• Genotyping error modeling: Accounts for genotyping error rates to improve accuracy of ROH detection.
• Length-based classification: Includes a module that classifies ROH into biologically meaningful length-based categories.
• Performance evaluation: Methodology performance has been assessed using simulations.
• Implementation: Developed in C++.

Scientific Applications:

• Population history inference: Infers autozygosity patterns indicative of demographic events such as bottlenecks and founder effects.
• Mapping recessive loci: Facilitates identification of recessive loci relevant to Mendelian and complex diseases.
• Clinical genetics and evolutionary biology: Supports analyses of inbreeding, autozygosity, and their consequences in clinical and evolutionary studies.

Methodology:

Implements the model-based approach of Pemberton et al., 2012, incorporating population-specific parameters and genotyping error rates, includes a length-based ROH classification module, and was evaluated using simulations; implemented in C++.