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General purpose model and a computer program for combined segregation and path analysis (SEGPATH): automatically

M A Province1, D C Rao

  • 1Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri 63110, USA.

Genetic Epidemiology
|January 1, 1995
PubMed
Summary
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SEGPATH is a flexible computer program for genetic epidemiology, enabling the creation of complex models for pedigree data analysis. It supports various analyses, including segregation and path analysis, accommodating diverse data structures and research questions.

Area of Science:

  • Genetic Epidemiology
  • Computational Biology
  • Biostatistics

Background:

  • Genetic epidemiological models are crucial for understanding disease inheritance and genetic influences.
  • Existing software may lack flexibility in handling complex pedigree structures and diverse analytical needs.

Purpose of the Study:

  • To develop a general-purpose model and flexible computer program, SEGPATH, for creating and implementing genetic epidemiological models.
  • To provide a tool capable of handling complex pedigree data and various analytical approaches.

Main Methods:

  • Development of SEGPATH, a computer program generating analysis programs for linear models of pedigree data.
  • Implementation of a flexible model-specification syntax.
  • Support for segregation analysis, path analysis, and combined analyses.

Related Experiment Videos

  • Accommodation of multivariate phenotypes, environmental indices, covariates, and measured genotypes.

    • Main Results:

    • SEGPATH can generate programs for complex genetic models, including population heterogeneity, repeated-measures, longitudinal, auto-regressive, developmental, and gene-by-environment interaction models.
    • The program handles arbitrarily complex pedigree structures and missing data.
    • Ascertainment corrections can be applied to phenotypes and other measures.
    • The general syntax allows application to non-genetic hierarchical models (e.g., longitudinal, time series).

    Conclusions:

    • SEGPATH offers a versatile and powerful platform for genetic epidemiological research.
    • Its flexibility extends to various complex data structures and analytical models, enhancing the study of genetic and environmental factors.
    • The program's applicability to non-genetic hierarchical data broadens its utility across scientific disciplines.