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Applied bioinformatic and statistica...

Webb, Bradley Todd.

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Applied bioinformatic and statistical approaches to complex disorder gene mapping.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Applied bioinformatic and statistical approaches to complex disorder gene mapping./
Author:	Webb, Bradley Todd.
Description:	149 p.
Notes:	Director: Michael C. Neale.
Contained By:	Dissertation Abstracts International64-06B.
Subject:	Biology, Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3094845

Applied bioinformatic and statistical approaches to complex disorder gene mapping.
Webb, Bradley Todd.

Applied bioinformatic and statistical approaches to complex disorder gene mapping. - 149 p.

Director: Michael C. Neale.

Thesis (Ph.D.)--Virginia Commonwealth University, 2003.

There has been great success in identifying the molecular variants that give rise to Mendelian disorders such as cystic fibrosis and Huntingtons disease. However, the same approaches have not been as successful when applied to complex disorders. A number of explanations and solutions have been proposed. Current challenges include but are not limited to; (1) the linkage regions are broad and contain many genes, (2) these same linkage results do not satisfy proposed criteria for statistical significance, and (3) the basic genetic architecture is still not understood. Schizophrenia is as an example of a complex disorder and was the phenotype used to attempt to address each of these issues. First, bioinformatics and data integration of a variety of types of evidence was used to prioritize candidate genes and polymorphisms in a large linked region. Second, the significance of linkage results was determined empirically. Finally, knowledge of a proposed schizophrenia risk variant was used to clarify linkage evidence in another region of the genome. The results of this research show; (1) bioinformatics tools can be used to rapidly prioritize genes in a large linked region, (2) the NPL Z-score is not distributed as a standard normal, (3) stratification of families based on a proposed <italic>DTNBP1</italic> risk haplotype on chromosome 6 increases the evidence for linkage on chromosome 8, and (4) the elusive goal of genome-wide significant linkage evidence is demonstrated via simulation. Each of these steps has advanced the goal of identifying additional schizophrenia susceptibility loci and understanding the genetic architecture of a socially and economically important disorder. Further, the approaches are general and can be applied to any complex disorder or trait.Subjects--Topical Terms:

1018416
Biology, Biostatistics.

Applied bioinformatic and statistical approaches to complex disorder gene mapping.
LDR:02714nam 2200277 a 45 001 929837
005 20110427
008 110427s2003 eng d
035 $a (UnM)AAI3094845
035 $a AAI3094845
040 $a UnM $c UnM
100 1 $a Webb, Bradley Todd. $3 1253323
245 1 0 $a Applied bioinformatic and statistical approaches to complex disorder gene mapping.
300 $a 149 p.
500 $a Director: Michael C. Neale.
500 $a Source: Dissertation Abstracts International, Volume: 64-06, Section: B, page: 2500.
502 $a Thesis (Ph.D.)--Virginia Commonwealth University, 2003.
520 $a There has been great success in identifying the molecular variants that give rise to Mendelian disorders such as cystic fibrosis and Huntingtons disease. However, the same approaches have not been as successful when applied to complex disorders. A number of explanations and solutions have been proposed. Current challenges include but are not limited to; (1) the linkage regions are broad and contain many genes, (2) these same linkage results do not satisfy proposed criteria for statistical significance, and (3) the basic genetic architecture is still not understood. Schizophrenia is as an example of a complex disorder and was the phenotype used to attempt to address each of these issues. First, bioinformatics and data integration of a variety of types of evidence was used to prioritize candidate genes and polymorphisms in a large linked region. Second, the significance of linkage results was determined empirically. Finally, knowledge of a proposed schizophrenia risk variant was used to clarify linkage evidence in another region of the genome. The results of this research show; (1) bioinformatics tools can be used to rapidly prioritize genes in a large linked region, (2) the NPL Z-score is not distributed as a standard normal, (3) stratification of families based on a proposed <italic>DTNBP1</italic> risk haplotype on chromosome 6 increases the evidence for linkage on chromosome 8, and (4) the elusive goal of genome-wide significant linkage evidence is demonstrated via simulation. Each of these steps has advanced the goal of identifying additional schizophrenia susceptibility loci and understanding the genetic architecture of a socially and economically important disorder. Further, the approaches are general and can be applied to any complex disorder or trait.
590 $a School code: 2383.
650 4 $a Biology, Biostatistics. $3 1018416
650 4 $a Biology, Genetics. $3 1017730
650 4 $a Biology, Molecular. $3 1017719
690 $a 0307
690 $a 0308
690 $a 0369
710 2 0 $a Virginia Commonwealth University. $3 1018010
773 0 $t Dissertation Abstracts International $g 64-06B.
790 $a 2383
790 1 0 $a Neale, Michael C., $e advisor
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3094845