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Using Wavelet-transforms to Improve Power for Linkage Disequilibrium >> MappingUsing Wavelet-transforms to Improve Power for Linkage Disequilibrium Using Wavelet-transforms to Improve Power for Linkage Disequilibrium Mapping

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Abstract:

We develop a powerful novel statistical method to identify genetic variants related to disease..
The new method uses wavelet-transforms on genotypes, with minimal degrees of freedom, to construct a weighted test statistic which captures significant information from multiple gene loci.Simulation is used to compare the power of the new procedure to existing, less general methods. The new statistic has significantly improved power.
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Association:
Name: The Mathematical Association of America MathFest
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http://www.maa.org


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URL: http://citation.allacademic.com/meta/p275358_index.html
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MLA Citation:

dai, yilin. "Using Wavelet-transforms to Improve Power for Linkage Disequilibrium >> MappingUsing Wavelet-transforms to Improve Power for Linkage Disequilibrium Using Wavelet-transforms to Improve Power for Linkage Disequilibrium Mapping" Paper presented at the annual meeting of the The Mathematical Association of America MathFest, TBA, Madison, Wisconsin, Jul 28, 2008 <Not Available>. 2013-12-14 <http://citation.allacademic.com/meta/p275358_index.html>

APA Citation:

dai, y. , 2008-07-28 "Using Wavelet-transforms to Improve Power for Linkage Disequilibrium >> MappingUsing Wavelet-transforms to Improve Power for Linkage Disequilibrium Using Wavelet-transforms to Improve Power for Linkage Disequilibrium Mapping" Paper presented at the annual meeting of the The Mathematical Association of America MathFest, TBA, Madison, Wisconsin <Not Available>. 2013-12-14 from http://citation.allacademic.com/meta/p275358_index.html

Publication Type: Graduate Student Paper
Abstract: We develop a powerful novel statistical method to identify genetic variants related to disease..
The new method uses wavelet-transforms on genotypes, with minimal degrees of freedom, to construct a weighted test statistic which captures significant information from multiple gene loci.Simulation is used to compare the power of the new procedure to existing, less general methods. The new statistic has significantly improved power.

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