Many genetic traits that are of greatest medical or economic importance are complex quantitative traits, such as weight, blood pressure, or susceptibility to disease. Such traits are usually affected by more than one gene. They are also usually affected by non-genetic factors such as the environment. They are typically described as a numerical value rather than as a set of descriptive names. In recent years, it has become feasible to identify many of the individual genes that contribute to complex traits. These genes are known as quantitative trait loci. This laboratory has written two software packages designed to aid the identification and characterization of these genes in organisms which provide models for human disease. One of these packages is Map Manager QTX, which is desktop software for Windows or Mac OS. The other is WebQTL, a Web-based system available at http://webqtl.roswellpark.org. Both of these packages are easy to use, but offer only the simpler statistical methods available for analysis of complex traits. ? ? To make more sophisticated statistical methods available to geneticists, we propose to develop graphic user interfaces and other enhancements for an existing statistical package called R/qtl. R/qtl, an extension of the widely used R statistical system, already implements many methods for complex trait analysis and further development is planned. The proposed software will make these functions accessible to geneticists and medical scientists. In addition, the proposed software will extend R/qtl so that it can use the power of a cluster of networked computers to perform calculations that are currently too time-consuming. ? ?

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Biotechnology Resource Grants (P41)
Project #
2P41HG001656-06
Application #
6731243
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Brooks, Lisa
Project Start
1997-09-01
Project End
2006-08-31
Budget Start
2004-09-24
Budget End
2005-08-31
Support Year
6
Fiscal Year
2004
Total Cost
$198,624
Indirect Cost
Name
University of Tennessee Health Science Center
Department
Pathology
Type
Schools of Medicine
DUNS #
941884009
City
Memphis
State
TN
Country
United States
Zip Code
38163
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Manly, Kenneth F; Nettleton, Dan; Hwang, J T Gene (2004) Genomics, prior probability, and statistical tests of multiple hypotheses. Genome Res 14:997-1001
Manly, K F (2000) Mathematica packages for simulation of experimental genetics. Bioinformatics 16:408-10