Statistical aspects of human gene mapping in the presence of errors [electronic resource] / Harald Heinz Herbert Goring

Goring, Harald Heinz Herbert
Bib ID
vtls000568595
稽核項
217 p.
電子版
附註項
數位化論文典藏聯盟
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$a Source: Dissertation Abstracts International, Volume: 61-05, Section: B, page: 2353.
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$a Adviser:  Jurg Ott.
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$a Thesis (Ph.D.)--Columbia University, 2000.
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$a Errors of various kinds cannot be completely avoided in human gene mapping studies. Generally, such errors negatively affect the analysis of linkage and/or linkage disequilibrium, by reducing the power to map loci, biasing parameter value estimates and/or increasing the risk of false positive findings. It is therefore important to develop statistical methods which are robust to such errors.
520
$a In this dissertation, seven papers about statistical aspects of gene mapping are presented, with a primary focus on how various types of errors can be treated in the statistical analysis. The first paper is a review of human gene mapping, giving an overview of the field and its current challenges. Misspecifications in pedigree structure are dealt with in the second paper, which outlines a method for detection of non-sibs in sib pair studies where the parents are not genotyped. In the third paper (as yet unpublished), a multipoint linkage disequilibrium method for analysis of haplotypes in the presence of uncertainty about trait locus alleles is described. The fourth paper outlines a means of mitigating the effects of inaccurate assumptions about the phenotype-genotype relationships of a trait and one underlying trait locus. The proposed model allows “model-based” multipoint analysis to be as robust to errors in mode of inheritance assumptions as “model-based” two-point analysis. A similar model, but for the treatment of marker genotyping errors, is described in the fifth paper. The sixth paper proposes a general framework for handling parameters characterizing the markers and their map, when the values of these parameters cannot be determined with certainty a priori. Lastly, the seventh paper demonstrates the equivalence of certain “model-based” and “model-free” analysis methods in a variety of situations, and describes more powerful, efficient and well-behaved likelihood-based analogs of conventional “model-free” methods.
520
$a Taken together, the chapters in this dissertation cover a wide spectrum of statistical issues in human gene mapping. It is hoped that this work will prove to be of practical value to investigators trying to map human genes. Most outlined ideas are implemented in software.
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$a 數位化論文典藏聯盟 $b PQDT $c 中山大學(2001~2002)
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$a Biology, Genetics.
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$a Statistics.
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$a Biology, Biostatistics.
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$a Ott, Jurg, $e advisor
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$a Columbia University.
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標題
摘要
Errors of various kinds cannot be completely avoided in human gene mapping studies. Generally, such errors negatively affect the analysis of linkage and/or linkage disequilibrium, by reducing the power to map loci, biasing parameter value estimates and/or increasing the risk of false positive findings. It is therefore important to develop statistical methods which are robust to such errors.
In this dissertation, seven papers about statistical aspects of gene mapping are presented, with a primary focus on how various types of errors can be treated in the statistical analysis. The first paper is a review of human gene mapping, giving an overview of the field and its current challenges. Misspecifications in pedigree structure are dealt with in the second paper, which outlines a method for detection of non-sibs in sib pair studies where the parents are not genotyped. In the third paper (as yet unpublished), a multipoint linkage disequilibrium method for analysis of haplotypes in the presence of uncertainty about trait locus alleles is described. The fourth paper outlines a means of mitigating the effects of inaccurate assumptions about the phenotype-genotype relationships of a trait and one underlying trait locus. The proposed model allows “model-based” multipoint analysis to be as robust to errors in mode of inheritance assumptions as “model-based” two-point analysis. A similar model, but for the treatment of marker genotyping errors, is described in the fifth paper. The sixth paper proposes a general framework for handling parameters characterizing the markers and their map, when the values of these parameters cannot be determined with certainty a priori. Lastly, the seventh paper demonstrates the equivalence of certain “model-based” and “model-free” analysis methods in a variety of situations, and describes more powerful, efficient and well-behaved likelihood-based analogs of conventional “model-free” methods.
Taken together, the chapters in this dissertation cover a wide spectrum of statistical issues in human gene mapping. It is hoped that this work will prove to be of practical value to investigators trying to map human genes. Most outlined ideas are implemented in software.
附註
Source: Dissertation Abstracts International, Volume: 61-05, Section: B, page: 2353.
Adviser: Jurg Ott.
Thesis (Ph.D.)--Columbia University, 2000.
數位化論文典藏聯盟
合著者
ISBN/ISSN
0599751649