GeneticsPed

GeneticsPed provides functions to handle and analyze pedigree data in R, compute relationship coefficients and inbreeding coefficients, and integrate pedigree information within the Bioconductor ecosystem for genetic and population-genetic research.

Key Features:

• Pedigree Data Management: Classes and methods to input, store, manipulate, and visualize complex family structures for downstream genetic analyses.
• Calculation of Genetic Relationship Measures: Functions to compute relationship coefficients and inbreeding coefficients for individuals within pedigrees.
• Interoperability with Bioconductor Packages: Integration with the Bioconductor ecosystem, enabling use alongside over 934 Bioconductor packages.
• R Implementation: Implemented in the R statistical programming language as part of the Bioconductor project.

Scientific Applications:

• Hereditary disease studies: Analysis of familial inheritance patterns and relatedness to support investigations of genetic disorders.
• Population genetics: Assessment of relatedness and inbreeding within populations to inform studies of genetic structure and diversity.
• Evolutionary biology: Use of pedigree-derived relationship measures to investigate genealogical patterns and evolutionary dynamics.
• Genetic diversity assessment: Evaluation of inbreeding coefficients and relationship measures to quantify genetic diversity within and between pedigrees.

Methodology:

Implemented in R within the Bioconductor framework and subjected to rigorous initial review and continuous automated testing of its components.