BayesMendel

BayesMendel predicts the probability that an individual carries inherited genetic variants and estimates disease risk from family history using Mendelian genetics and statistical models.

Key Features:

• Implementation: Implemented as an R package with an object-oriented structure.
• Supported syndromes: Includes models for breast-ovarian cancer syndrome and hereditary non-polyposis colorectal cancer syndrome.
• Penetrance and prevalence estimates: Incorporates penetrance and prevalence estimates for genes associated with the supported syndromes.
• Customizable genetic parameters: Allows modification of input genetic parameters for population- or study-specific analyses.
• Extensible modeling platform: Enables development and implementation of custom Mendelian models for novel syndromes and local subpopulations without reprogramming core statistical analyses.

Scientific Applications:

• Clinical genetics: Estimates individual carrier and disease probabilities from family history and genetic data to inform risk assessment and genetic counseling.
• Genetic epidemiology and research: Supports development and evaluation of new Mendelian models to study genotype–phenotype relationships across populations.

Methodology:

Combines classical Mendelian inheritance principles with statistical modeling to estimate carrier probabilities and disease risk from family history and genetic data using specified penetrance and prevalence parameters.