skip to content
Analysis and application of linkage disequilibrium in population and statistical genetics Preview this item
ClosePreview this item
Checking...

Analysis and application of linkage disequilibrium in population and statistical genetics

Author: Teng Leng Jonathan Kang; Noah Rosenberg; Marcus W Feldman; Hua Tang; Stanford University. Department of Biology.
Publisher: [Stanford, California] : [Stanford University], 2018. ©2018
Dissertation: Ph. D. Stanford University 2018
Edition/Format:   Thesis/dissertation : Document : Thesis/dissertation : eBook   Computer File : English
Summary:
Linkage disequilibrium (LD) is the non-random association of alleles at different genetic loci. This dissertation consists of three projects that relate to the analysis and application of LD on various topics within population and statistical genetics. Various measures of LD have been proposed in the literature, each with different arguments favoring its use. Chapter 2 employs a theoretical approach to examine  Read more...
Rating:

(not yet rated) 0 with reviews - Be the first.

Find a copy online

Links to this item

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Genre/Form: Academic theses
Material Type: Document, Thesis/dissertation, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Teng Leng Jonathan Kang; Noah Rosenberg; Marcus W Feldman; Hua Tang; Stanford University. Department of Biology.
OCLC Number: 1050949466
Notes: Submitted to the Department of Biology.
Description: 1 online resource
Responsibility: Teng Leng Jonathan Kang.

Abstract:

Linkage disequilibrium (LD) is the non-random association of alleles at different genetic loci. This dissertation consists of three projects that relate to the analysis and application of LD on various topics within population and statistical genetics. Various measures of LD have been proposed in the literature, each with different arguments favoring its use. Chapter 2 employs a theoretical approach to examine mathematical properties of five different measures of LD. These results help place the use of various LD statistics into their proper contexts, and provide a mathematical basis for comparing their values. Next, the presence of LD in genomes can be leveraged for a number of different applications in statistical genetics. Chapter 3 examines one such example in genetic imputation. Specifically, we ask the question of how to optimally select a subset of a study sample for sequencing when choosing an internal reference panel for imputation, in order to maximize the eventual imputation accuracy. We compare two algorithms--maximizing phylogenetic diversity (PD) and minimizing average distance to the closest leaf (ADCL)--and conclude that while both algorithms give better imputation results as compared to randomly selecting haplotypes to be included in the reference panel, imputation accuracy is the highest when minimizing ADCL is used as the method for panel selection. Finally, LD in genomes can produce genetic signatures that may be suggestive of certain demographic processes. Genetic linkage results in the preservation of homozygous segments in the genome that are produced as the result of genomic sharing, which can then be detected as runs of homozygosity (ROH). Chapter 4 analyzes the distribution of ROH lengths in a sample of worldwide Jewish and non-Jewish populations, and employs a model-based clustering method to classify the ROH in a given population into three classes (short, intermediate, and long) based on length. Furthermore, for a subset of the Jewish populations in this study, we were able to obtain estimates of demographic rates of consanguinity (as indicated by the rates of close-relative unions). We find that the level of consanguinity in those populations is predictive of long ROH, thus finding genetic signatures of mating patterns that existed in a population's history. Making use of theoretical, computational, and statistical approaches, these chapters together provide a wide-ranging account of different aspects of LD, as related to their respective applications within the field.

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.
Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


Primary Entity

<http://www.worldcat.org/oclc/1050949466> # Analysis and application of linkage disequilibrium in population and statistical genetics
    a bgn:Thesis, schema:MediaObject, schema:CreativeWork, schema:Book, pto:Web_document ;
    bgn:inSupportOf "" ;
    library:oclcnum "1050949466" ;
    library:placeOfPublication <http://id.loc.gov/vocabulary/countries/cau> ;
    schema:author <http://experiment.worldcat.org/entity/work/data/5418078221#Person/kang_teng_leng_jonathan> ; # Teng Leng Jonathan Kang
    schema:contributor <http://experiment.worldcat.org/entity/work/data/5418078221#Person/rosenberg_noah> ; # Noah Rosenberg
    schema:contributor <http://experiment.worldcat.org/entity/work/data/5418078221#Organization/stanford_university_department_of_biology> ; # Stanford University. Department of Biology.
    schema:contributor <http://experiment.worldcat.org/entity/work/data/5418078221#Person/tang_hua> ; # Hua Tang
    schema:contributor <http://experiment.worldcat.org/entity/work/data/5418078221#Person/feldman_marcus_w> ; # Marcus W. Feldman
    schema:copyrightYear "2018" ;
    schema:datePublished "2018" ;
    schema:description "Linkage disequilibrium (LD) is the non-random association of alleles at different genetic loci. This dissertation consists of three projects that relate to the analysis and application of LD on various topics within population and statistical genetics. Various measures of LD have been proposed in the literature, each with different arguments favoring its use. Chapter 2 employs a theoretical approach to examine mathematical properties of five different measures of LD. These results help place the use of various LD statistics into their proper contexts, and provide a mathematical basis for comparing their values. Next, the presence of LD in genomes can be leveraged for a number of different applications in statistical genetics. Chapter 3 examines one such example in genetic imputation. Specifically, we ask the question of how to optimally select a subset of a study sample for sequencing when choosing an internal reference panel for imputation, in order to maximize the eventual imputation accuracy. We compare two algorithms--maximizing phylogenetic diversity (PD) and minimizing average distance to the closest leaf (ADCL)--and conclude that while both algorithms give better imputation results as compared to randomly selecting haplotypes to be included in the reference panel, imputation accuracy is the highest when minimizing ADCL is used as the method for panel selection. Finally, LD in genomes can produce genetic signatures that may be suggestive of certain demographic processes. Genetic linkage results in the preservation of homozygous segments in the genome that are produced as the result of genomic sharing, which can then be detected as runs of homozygosity (ROH). Chapter 4 analyzes the distribution of ROH lengths in a sample of worldwide Jewish and non-Jewish populations, and employs a model-based clustering method to classify the ROH in a given population into three classes (short, intermediate, and long) based on length. Furthermore, for a subset of the Jewish populations in this study, we were able to obtain estimates of demographic rates of consanguinity (as indicated by the rates of close-relative unions). We find that the level of consanguinity in those populations is predictive of long ROH, thus finding genetic signatures of mating patterns that existed in a population's history. Making use of theoretical, computational, and statistical approaches, these chapters together provide a wide-ranging account of different aspects of LD, as related to their respective applications within the field."@en ;
    schema:exampleOfWork <http://worldcat.org/entity/work/id/5418078221> ;
    schema:genre "Academic theses"@en ;
    schema:inLanguage "en" ;
    schema:name "Analysis and application of linkage disequilibrium in population and statistical genetics"@en ;
    schema:productID "1050949466" ;
    schema:url <http://purl.stanford.edu/xr581vh0975> ;
    wdrs:describedby <http://www.worldcat.org/title/-/oclc/1050949466> ;
    .


Related Entities

<http://experiment.worldcat.org/entity/work/data/5418078221#Organization/stanford_university_department_of_biology> # Stanford University. Department of Biology.
    a schema:Organization ;
    schema:name "Stanford University. Department of Biology." ;
    .

<http://experiment.worldcat.org/entity/work/data/5418078221#Person/feldman_marcus_w> # Marcus W. Feldman
    a schema:Person ;
    schema:familyName "Feldman" ;
    schema:givenName "Marcus W." ;
    schema:name "Marcus W. Feldman" ;
    .

<http://experiment.worldcat.org/entity/work/data/5418078221#Person/kang_teng_leng_jonathan> # Teng Leng Jonathan Kang
    a schema:Person ;
    schema:familyName "Kang" ;
    schema:givenName "Teng Leng Jonathan" ;
    schema:name "Teng Leng Jonathan Kang" ;
    .

<http://experiment.worldcat.org/entity/work/data/5418078221#Person/rosenberg_noah> # Noah Rosenberg
    a schema:Person ;
    schema:familyName "Rosenberg" ;
    schema:givenName "Noah" ;
    schema:name "Noah Rosenberg" ;
    .

<http://www.worldcat.org/title/-/oclc/1050949466>
    a genont:InformationResource, genont:ContentTypeGenericResource ;
    schema:about <http://www.worldcat.org/oclc/1050949466> ; # Analysis and application of linkage disequilibrium in population and statistical genetics
    schema:dateModified "2019-06-14" ;
    void:inDataset <http://purl.oclc.org/dataset/WorldCat> ;
    .


Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.