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Languages : en
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Author: Han Hao
Publisher:
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Category :
Languages : en
Pages :
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Quantitative trait loci (QTL) mapping is the process of detecting genetic variants that regulate complex traits. Among all complex traits with continuous values, function-valued traits that undergo developmental processes are commonly seen in growth analysis, shape analysis, network analysis, and clinical trials. Functional mapping is a statistical tool for mapping QTLs involved with function-valued phenotypic traits. The utility of functional mapping can be displayed when the phenotypic traits represent developmental processes and can be modeled by either parametric or nonparametric curves.In this dissertation, we focus on the application of functional mapping and the development of computational frameworks in different types of function-valued traits. In Chapter 2, we deal with the situation where the trait values follow a parametric trend. A Richard curve is used to model rice height growth, and QTLs are examined for their association with the onset, offset and duration of the developmentaol process using a Gaussian mixture model. In Chapter 3, the trait values do not have a parametric form. The contour of mei leaves is modeled using Fourier basis expansion, and QTLs are examined for their association with shape development using a high-dimensional analysis of variance (HANOVA) approach. In Chapter 4 and Chapter 5, we study the interactions between two function-valued traits. The growth of two interacting traits is modeled with ordinary differential equation (ODE) systems, and QTLs are examined for their association with the type and intensity of such interactions using a generalized profiling approach.
Author: Jong Rho
Publisher: CRC Press
ISBN: 1420085603
Category : Medical
Languages : en
Pages : 684
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Epilepsy has afflicted humankind throughout recorded history; yet, it is only in the last half-century, that significant progress has been made in our basic understanding of the epileptic brain. Pivotal advances in drug development and surgical techniques, as well as the emergence of innovative approaches such as electrical stimulation of the nervo
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309060354
Category : Science
Languages : en
Pages : 85
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Printbegrænsninger: Der kan printes 10 sider ad gangen og max. 40 sider pr. session.
Author: Juhyun Kim
Publisher:
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Category :
Languages : en
Pages : 130
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Variance component models are a fundamental topic in statistical genetics. These models enable us to estimate the underlying heritability of a phenotype, adjust for confounding in association testing, and assess the strength of effects of a set of genetic markers on a phenotype. Under the overarching theme of variance component models, this dissertation aims to elucidate the genetic architecture of complex diseases and traits by developing and applying variance component model-based methods to analyze high-dimensional genomic data. In the first half of the dissertation, we propose a variance component selection framework that jointly models and prioritizes a set of genetic markers that are associated with quantitative traits. The second half of the dissertation is devoted to quantifying the heritability of diabetes complications. We use various heritability estimation methods, some of which are based on variance component models.
Author: Matthew B. Hamilton
Publisher: John Wiley & Sons
ISBN: 111843689X
Category : Science
Languages : en
Pages : 501
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Now updated for its second edition, Population Genetics is the classic, accessible introduction to the concepts of population genetics. Combining traditional conceptual approaches with classical hypotheses and debates, the book equips students to understand a wide array of empirical studies that are based on the first principles of population genetics. Featuring a highly accessible introduction to coalescent theory, as well as covering the major conceptual advances in population genetics of the last two decades, the second edition now also includes end of chapter problem sets and revised coverage of recombination in the coalescent model, metapopulation extinction and recolonization, and the fixation index.
Author: Reynolds, M.P.
Publisher: CIMMYT
ISBN:
Category :
Languages : en
Pages : 100
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Author: Jennifer S. Singh
Publisher: U of Minnesota Press
ISBN: 1452949824
Category : Social Science
Languages : en
Pages : 323
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Is there a gene for autism? Despite a billion-dollar, twenty-year effort to find out—and the more elusive the answer, the greater the search seems to become—no single autism gene has been identified. In Multiple Autisms, Jennifer S. Singh sets out to discover how autism emerged as a genetic disorder and how this affects those who study autism and those who live with it. This is the first sustained analysis of the practices, politics, and meaning of autism genetics from a scientific, cultural, and social perspective. In 2004, when Singh began her research, the prevalence of autism was reported as 1 in 150 children. Ten years later, the number had jumped to 1 in 100, with the disorder five times more common in boys than in girls. Meanwhile the diagnosis changed to “autistic spectrum disorders,” and investigations began to focus more on genomics than genetics, less on single genes than on hundreds of interacting genes. Multiple Autisms charts this shift and its consequences through nine years of ethnographic observations, analysis of scientific and related literatures, and morethan seventy interviews with autism scientists, parents of children with autism, and people on the autism spectrum. The book maps out the social history of parental activism in autism genetics, the scientific optimism about finding a gene for autism and the subsequent failure, and the cost in personal and social terms of viewing and translating autism through a genomic lens. How is genetic information useful to people living with autism? By considering this question alongside the scientific and social issues that autism research raises, Singh’s work shows us the true reach and implications of a genomic gaze.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309183626
Category : Mathematics
Languages : en
Pages : 134
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Book Description
Over three hundred years ago, Galileo is reported to have said, "The laws of nature are written in the language of mathematics." Often mathematics and science go hand in hand, with one helping develop and improve the other. Discoveries in science, for example, open up new advances in statistics, computer science, operations research, and pure and applied mathematics which in turn enabled new practical technologies and advanced entirely new frontiers of science. Despite the interdependency that exists between these two disciplines, cooperation and collaboration between mathematical scientists and scientists have only occurred by chance. To encourage new collaboration between the mathematical sciences and other fields and to sustain present collaboration, the National Research Council (NRC) formed a committee representing a broad cross-section of scientists from academia, federal government laboratories, and industry. The goal of the committee was to examine the mechanisms for strengthening interdisciplinary research between mathematical sciences and the sciences, with a strong focus on suggesting the most effective mechanisms of collaboration. Strengthening the Linkages Between the Sciences and the Mathematical Sciences provides the findings and recommendations of the committee as well as case studies of cross-discipline collaboration, the workshop agenda, and federal agencies that provide funding for such collaboration.
Author: Kodi Taraszka
Publisher:
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Category :
Languages : en
Pages : 0
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Exploring how genetic architecture shapes complex traits and diseases is a central premise of human genetics. Over the years, genome-wide association studies (GWAS) have enabled the discovery of numerous genetic variants associated with a variety of complex traits. In addition to the large array of traits analyzed, GWAS in diverse ancestral populations have also seen a significant increase in sample sizes. These efforts led to tens of thousands of publicly available GWAS summary statistics whose known correlation structure could be leveraged for further discovery. In this dissertation, I present two novel methods for the meta-analysis of GWAS summary statistics as well as conduct a pan-cancer meta-analysis of somatic variant burden. For one method, I present a likelihood ratio test for the joint analysis of genetically correlated traits and provide a per trait interpretation framework of the omnibus association. For the other method, I present a Bayesian framework that improves fine mapping of significant associations for one trait by leveraging the complementary information from distinct ancestral backgrounds. In addition to these methods, I analyzed how clinical and polygenic germline features influence somatic variant burden within and across cancer types.
