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Future directions of research in statistical genetics
1Department of Human Genetics, University of California, Los Angeles, Gonda Neuroscience & Genetics Research Center, 695 Charles E. Young Drive South, Suite 6506, Los Angeles, California 90095-7088, USA. horvath_stefan@hotmail.com
Statistics in Medicine
|December 21, 2000
Summary
Statistical genetics advances with better DNA data and new technologies. Functional mapping strategies leverage gene function knowledge for complex disease gene discovery.
Area of Science:
- Statistical genetics
- Genomics
- Bioinformatics
Background:
- Rapid advancements in genetic data, including human DNA sequencing, and new technologies like microarray technology are transforming statistical genetics.
- Existing meiotic mapping techniques require adaptation to leverage improved data, such as extending allelic association studies to multiple markers.
Purpose of the Study:
- To introduce and explain functional mapping as a novel gene mapping strategy.
- To highlight the potential of functional mapping for identifying complex disease genes by bridging genotype and phenotype information.
Main Methods:
- Utilizing pathway fractions as intermediate data between genotype and phenotype.
- Applying methods from whole-genome gene expression studies to illustrate functional mapping concepts.
Main Results:
- Functional mapping offers a promising approach for complex disease gene discovery.
- The integration of gene function knowledge enables new mapping strategies.
Conclusions:
- Functional mapping, by using pathway information, represents a significant advancement in gene mapping.
- Adapting to new data and technologies is crucial for the future of statistical genetics and disease gene identification.