QUANTITATIVE ASSOCIATION METHODS FOR GENE MAPPING

Project: Research project

Project Details

Description

Determining the causes of common complex human diseases and traits that
are influenced by several genetic and environmental factors has immense
public health benefits, ranging from prevention to earlier detection and
treatment. However, the current quantitative methods used to analyze
complex diseases are limited in their power, their flexibility to
account for multiple genetic and environmental factors, and their
robustness to departures from sometimes untestable assumptions. The
overall objectives of this proposed research program are to facilitate
"The Future of Genetic Studies of Complex Human Diseases" by developing
innovative statistical methods and software that can be used by
biomedical researchers to design and analyze family-based association
studies that take advantage of both linkage and linkage disequilibrium.
The four specific aims of this proposed research program encompass the
development of the necessary quantitative tools:

1. Development of robust semi-parametric statistical methods that will
be used to analyze family-based genetic association studies, and which
account for many of the complexities of family-based studies of common
diseases, such as different types of traits (e.g., binary, polytomous,
ordinal, censored age-dependent, and quantitative traits), environmental
risk factors, gene-gene and gene-environment interactions, and residual
correlations among pedigree members; 2. Development of statistical
methods and simulation routines that will be used to determine the
design of genetic association studies; 3. Development of user-friendly
computer software that implements these procedures; 4. Development of
documentation that describes the implemented statistical methodology,
how to use the developed software, and how to interpret the results from
the analyses. The advantages of this proposed research, over those
currently used to identify and characterize genes of complex diseases,
are that it will offer a more powerful and flexible method to find these
types of genes.
StatusFinished
Effective start/end date2/1/991/31/03

ASJC

  • Medicine(all)
  • Dentistry(all)