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Author: Lisa Anne Brown
Publisher:
ISBN:
Category :
Languages : en
Pages : 94
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Book Description
Genetic admixture occurs when two or more previously isolated populations combine to form an admixed population. The study of admixed populations can provide valuable insights into the complex relationship between environmental exposures, genetic background and complex traits. Gene mapping by linkage admixture disequilibrium, or admixture mapping, is a powerful approach for the identification of genetic loci influencing complex traits in ancestrally diverse populations. Admixture mapping leverages genomic heterogeneity among sampled individuals for improved gene discovery, where genetic loci with unusual deviations in local ancestry and that are significantly associated with a trait are identified. Admixture mapping can serve both as a primary method for discovery of novel genetic variants and as a complement to association mapping. In this dissertation, we thoroughly investigate the performance of existing statistical methods used for admixture mapping and we develop new methods that improve upon existing approaches. We also characterize the correlation structure of genetic loci in admixed populations and develop new genome-wide significance thresholds for admixture mapping under a range of models that should be useful for the future studies. Using real genotyping data in a large sample of African Americans, we find evidence of assortative mating, and in simulation studies with simulated phenotypes, we demonstrate that ancestry-related assortative can induce genome-wide inflation of admixture mapping test statistics and false positive associations. We also show how to appropriately adjust for this inflation and protect against spurious admixture associations. Finally, new linear and logistic mixed model methodology is developed for admixture mapping of quantitative and binary traits, respectively, in the presence of relatedness and population structure. We evaluate the performance of these methods through extensive simulation studies. The methods are applied to large-scale genetic studies of African American and Hispanic/Latino populations for genome-wide admixture mapping analyses where novel candidate loci for a variety of biomedical traits are identified.
Author: Lisa Anne Brown
Publisher:
ISBN:
Category :
Languages : en
Pages : 94
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Book Description
Genetic admixture occurs when two or more previously isolated populations combine to form an admixed population. The study of admixed populations can provide valuable insights into the complex relationship between environmental exposures, genetic background and complex traits. Gene mapping by linkage admixture disequilibrium, or admixture mapping, is a powerful approach for the identification of genetic loci influencing complex traits in ancestrally diverse populations. Admixture mapping leverages genomic heterogeneity among sampled individuals for improved gene discovery, where genetic loci with unusual deviations in local ancestry and that are significantly associated with a trait are identified. Admixture mapping can serve both as a primary method for discovery of novel genetic variants and as a complement to association mapping. In this dissertation, we thoroughly investigate the performance of existing statistical methods used for admixture mapping and we develop new methods that improve upon existing approaches. We also characterize the correlation structure of genetic loci in admixed populations and develop new genome-wide significance thresholds for admixture mapping under a range of models that should be useful for the future studies. Using real genotyping data in a large sample of African Americans, we find evidence of assortative mating, and in simulation studies with simulated phenotypes, we demonstrate that ancestry-related assortative can induce genome-wide inflation of admixture mapping test statistics and false positive associations. We also show how to appropriately adjust for this inflation and protect against spurious admixture associations. Finally, new linear and logistic mixed model methodology is developed for admixture mapping of quantitative and binary traits, respectively, in the presence of relatedness and population structure. We evaluate the performance of these methods through extensive simulation studies. The methods are applied to large-scale genetic studies of African American and Hispanic/Latino populations for genome-wide admixture mapping analyses where novel candidate loci for a variety of biomedical traits are identified.
Author: Chao Tian
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
There exists much variation in genetic ancestry within and between ethnic groups, which causes substantial population stratification to be present not only in recently admixed populations like African Americans but also in generally assumed homogeneous populations like European Americans. In Chapter One I reviewed the recent studies of measuring and using genetic ancestry in human complex disease studies. Genetics variations constitute an important basis for Admixture Mapping. Many complex diseases show population specific prevalence that could be due to the differences of particular disease-susceptible genes among founding populations of different ancestry. Statistical methods can be applied to infer the locus ancestry along the chromosome in admixed individuals and tests for the association of the locus ancestry with the disease in admixed population, so called admixture mapping. Admixture mapping requires a genome-wide panel of relatively evenly spaced markers that can distinguish the locus ancestral origins in admixed individuals. In Chapter Two and Chapter Three I introduced our defined genome-wide Single-Nucleotide-Polymorphism panels that can extract ancestry information mostly with the least markers for African American and Mexican American admixed populations. On the other hand, a consequence of population stratification is the potential for false allelic associations and thus the inconsistent reports across genome-wide association studies. Statistical methods can be applied to discern and correct for the individual ancestry differences using Genome-wide association panel. In Chapter Four I introduced our findings of the European substructures, which have significant genetic variation along the north to south and west to east geographic axis. One of our recent report showed that after accounting for genetic ancestry difference, some locus are no long associated to Rheumatoid Arthritis but they appeared as very strong candidates without accounting for the substructure. In Chapter Five I introduced our findings of the East Asian substructures. Our analysis showed that there exist genetic variations both between different East Asian groups and within the Han Chinese population. In Chapter Six I reviewed the current available methods and importance of accounting for ancestry in genome-wide association studies. In Chapter Seven, I discussed some implications and future research directions.
Author: Kelsey Grinde
Publisher:
ISBN:
Category :
Languages : en
Pages : 170
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Book Description
Understanding the genetic causes of human diseases and traits has long been of interest in the scientific community. However, the large majority of research in this area has been conducted in European populations. This dissertation focuses on developing statistical methods for genetic studies in admixed populations, such as African Americans and Hispanics/Latinos, that have been historically underrepresented in genetics research. The diverse, mixed ancestry of admixed populations presents unique opportunities for statistical inference, many of which are explored in this work. Here, we focus in particular on two important tasks: inferring genetic ancestry from genotype and sequence data, and identifying genetic variants associated with complex traits and diseases. We propose and evaluate methods for inferring local ancestry on chromosome X, correcting for multiple testing in genome-wide admixture mapping studies, and controlling for confounding by global ancestry in admixture mapping and genome-wide association studies in admixed populations. We motivate our proposed methods with theoretical results, simulation studies, and applications to genotype and whole genome sequence data from large studies of African American and Hispanic/Latino individuals. Our work provides solutions to a number of the statistical challenges posed by genetic studies in admixed populations, and we hope that our results will help guide future studies in these populations.
Author: Riyan Cheng
Publisher: Frontiers Media SA
ISBN: 2889712125
Category : Science
Languages : en
Pages : 148
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Book Description
Author: Mark Jobling
Publisher: Garland Science
ISBN: 1317952251
Category : Medical
Languages : en
Pages : 1557
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Book Description
Human Evolutionary Genetics is a groundbreaking text which for the first time brings together molecular genetics and genomics to the study of the origins and movements of human populations. Starting with an overview of molecular genomics for the non-specialist (which can be a useful review for those with a more genetic background), the book shows h
Author: Florian Frommlet
Publisher: Springer
ISBN: 1447153103
Category : Computers
Languages : en
Pages : 232
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Book Description
This timely text presents a comprehensive guide to genetic association, a new and rapidly expanding field that aims to elucidate how our genetic code (genotypes) influences the traits we possess (phenotypes). The book provides a detailed review of methods of gene mapping used in association with experimental crosses, as well as genome-wide association studies. Emphasis is placed on model selection procedures for analyzing data from large-scale genome scans based on specifically designed modifications of the Bayesian information criterion. Features: presents a thorough introduction to the theoretical background to studies of genetic association (both genetic and statistical); reviews the latest advances in the field; illustrates the properties of methods for mapping quantitative trait loci using computer simulations and the analysis of real data; discusses open challenges; includes an extensive statistical appendix as a reference for those who are not totally familiar with the fundamentals of statistics.
Author: David Siegmund
Publisher: Springer Science & Business Media
ISBN: 0387496866
Category : Medical
Languages : en
Pages : 337
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Book Description
This book details the statistical concepts used in gene mapping, first in the experimental context of crosses of inbred lines and then in outbred populations, primarily humans. It presents elementary principles of probability and statistics, which are implemented by computational tools based on the R programming language to simulate genetic experiments and evaluate statistical analyses. Each chapter contains exercises, both theoretical and computational, some routine and others that are more challenging. The R programming language is developed in the text.
Author: Pongsakorn Wangkumhang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Narayanaswamy Balakrishnan
Publisher: John Wiley & Sons
ISBN: 1118595963
Category : Medical
Languages : en
Pages : 953
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Book Description
Methods and Applications of Statistics in Clinical Trials, Volume 2: Planning, Analysis, and Inferential Methods includes updates of established literature from the Wiley Encyclopedia of Clinical Trials as well as original material based on the latest developments in clinical trials. Prepared by a leading expert, the second volume includes numerous contributions from current prominent experts in the field of medical research. In addition, the volume features: • Multiple new articles exploring emerging topics, such as evaluation methods with threshold, empirical likelihood methods, nonparametric ROC analysis, over- and under-dispersed models, and multi-armed bandit problems • Up-to-date research on the Cox proportional hazard model, frailty models, trial reports, intrarater reliability, conditional power, and the kappa index • Key qualitative issues including cost-effectiveness analysis, publication bias, and regulatory issues, which are crucial to the planning and data management of clinical trials
Author: David J. Balding
Publisher: John Wiley & Sons
ISBN: 1119429250
Category : Science
Languages : en
Pages : 1828
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Book Description
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
