Regression Based Methods To Map Quantitative Trait Loci Underlying Function Valued Phenotypes
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Regression Based Methods To Map Quantitative Trait Loci Underlying Function Valued Phenotypes
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Author :
language : en
Publisher:
Release Date : 2014
Regression Based Methods To Map Quantitative Trait Loci Underlying Function Valued Phenotypes written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Most statistical methods for QTL mapping focus on a single phenotype. However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time. While there exist methods for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models. This thesis is composed of two main parts. In the first part, I propose some simple approaches for QTL mapping with function-valued traits, including multiple-QTL models using a penalized likelihood approach. The methods are fast and maintain high power and precision. After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes. However there are two weaknesses. First, the methods do not work well when the curves are not smooth. Second, they do not take account of the correlation structure among time points. In the second part, I suggest a method to overcome those weaknesses, by smoothing the data set to reduce measurement error, and with functional Principal Component Analysis (PCA). We reduce the functional data into a small number of principal components without much loss of information. We can then proceed with QTL mapping on these dimension-reduced data. We consider four subsequent methods for analysis. First, we simply treat these multiple traits as independent. Second, we use multivariate QTL mapping method proposed by \citet{knott2000}, assuming that the transformed multivariate trait data follow a multivariate normal distribution. The third and fourth ideas are to take the average and maximum of LOD scores for each trait, as considered in the first part. I have implemented these methods in an R package, funqtl (github.com/ikwak2/funqtl ).
Quantitative Trait Loci
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Author : Nicola J. Camp
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-02-03
Quantitative Trait Loci written by Nicola J. Camp and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-03 with Medical categories.
In Quantitative Trait Loci: Methods and Protocols, a panel of highly experienced statistical geneticists demonstrate in a step-by-step fashion how to successfully analyze quantitative trait data using a variety of methods and software for the detection and fine mapping of quantitative trait loci (QTL). Writing for the nonmathematician, these experts guide the investigator from the design stage of a project onwards, providing detailed explanations of how best to proceed with each specific analysis, to find and use appropriate software, and to interpret results. Worked examples, citations to key papers, and variations in method ease the way to understanding and successful studies. Among the cutting-edge techniques presented are QTDT methods, variance components methods, and the Markov Chain Monte Carlo method for joint linkage and segregation analysis.
Big Data In Omics And Imaging
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Author : Momiao Xiong
language : en
Publisher: CRC Press
Release Date : 2018-06-14
Big Data In Omics And Imaging written by Momiao Xiong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-14 with Mathematics categories.
Big Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic and imaging data analysis and causal inference in big data era. Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), genome-wide expression studies (GWES), and epigenome-wide association studies (EWAS), the overall contribution of the new identified genetic variants is small and a large fraction of genetic variants is still hidden. Understanding the etiology and causal chain of mechanism underlying complex diseases remains elusive. It is time to bring big data, machine learning and causal revolution to developing a new generation of genetic analysis for shifting the current paradigm of genetic analysis from shallow association analysis to deep causal inference and from genetic analysis alone to integrated omics and imaging data analysis for unraveling the mechanism of complex diseases. FEATURES Provides a natural extension and companion volume to Big Data in Omic and Imaging: Association Analysis, but can be read independently. Introduce causal inference theory to genomic, epigenomic and imaging data analysis Develop novel statistics for genome-wide causation studies and epigenome-wide causation studies. Bridge the gap between the traditional association analysis and modern causation analysis Use combinatorial optimization methods and various causal models as a general framework for inferring multilevel omic and image causal networks Present statistical methods and computational algorithms for searching causal paths from genetic variant to disease Develop causal machine learning methods integrating causal inference and machine learning Develop statistics for testing significant difference in directed edge, path, and graphs, and for assessing causal relationships between two networks The book is designed for graduate students and researchers in genomics, epigenomics, medical image, bioinformatics, and data science. Topics covered are: mathematical formulation of causal inference, information geometry for causal inference, topology group and Haar measure, additive noise models, distance correlation, multivariate causal inference and causal networks, dynamic causal networks, multivariate and functional structural equation models, mixed structural equation models, causal inference with confounders, integer programming, deep learning and differential equations for wearable computing, genetic analysis of function-valued traits, RNA-seq data analysis, causal networks for genetic methylation analysis, gene expression and methylation deconvolution, cell –specific causal networks, deep learning for image segmentation and image analysis, imaging and genomic data analysis, integrated multilevel causal genomic, epigenomic and imaging data analysis.
Statistical Genetics Of Quantitative Traits
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Author : Rongling Wu
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-17
Statistical Genetics Of Quantitative Traits written by Rongling Wu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-17 with Science categories.
This book introduces the basic concepts and methods that are useful in the statistical analysis and modeling of the DNA-based marker and phenotypic data that arise in agriculture, forestry, experimental biology, and other fields. It concentrates on the linkage analysis of markers, map construction and quantitative trait locus (QTL) mapping, and assumes a background in regression analysis and maximum likelihood approaches. The strength of this book lies in the construction of general models and algorithms for linkage analysis, as well as in QTL mapping in any kind of crossed pedigrees initiated with inbred lines of crops.
Phenotypes And Genotypes
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Author : Florian Frommlet
language : en
Publisher: Springer
Release Date : 2016-02-12
Phenotypes And Genotypes written by Florian Frommlet and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-12 with Computers categories.
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.
Statistical Methods For Qtl Mapping
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Author : Zehua Chen
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Statistical Methods For Qtl Mapping written by Zehua Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Mathematics categories.
While numerous advanced statistical approaches have recently been developed for quantitative trait loci (QTL) mapping, the methods are scattered throughout the literature. Statistical Methods for QTL Mapping brings together many recent statistical techniques that address the data complexity of QTL mapping. After introducing basic genetics topics an
A Guide To Qtl Mapping With R Qtl
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Author : Karl W. Broman
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-21
A Guide To Qtl Mapping With R Qtl written by Karl W. Broman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-21 with Science categories.
Comprehensive discussion of QTL mapping concepts and theory Detailed instructions on the use of the R/qtl software, the most featured and flexible software for QTL mapping Two case studies illustrate QTL analysis in its entirety
Next Generation Plant Breeding
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Author : Yelda Ozden Çiftçi
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-09-26
Next Generation Plant Breeding written by Yelda Ozden Çiftçi and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-26 with Medical categories.
Following the green revolution and transgenic crop development, another revolutionary progress has been experienced in plant breeding in the last decade with the application of marker-assisted selection (MAS), next-generation sequencing (NGS), and gene editing techniques together with omic technologies, including genomics, transcriptomics, proteomics, and phenomics. Thus, this book is structured into two sections: "Marker-Assisted Breeding" and "RNA-seq and Gene Editing in Plants," which aim to provide a reference for students, instructors, and scientists on recent innovative advances in plant-breeding programs to cultivate crops for tomorrow.
Quantitative Trait Loci Analysis In Animals
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Author : Joel Ira Weller
language : en
Publisher: CABI
Release Date : 2009
Quantitative Trait Loci Analysis In Animals written by Joel Ira Weller and has been published by CABI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Technology & Engineering categories.
Quantitative Trait Loci (QTL) is a topic of major agricultural significance for efficient livestock production. This book covers various statistical methods that have been used or proposed for detection and analysis of QTL and marker-and gene-assisted selection in animal genetics and breeding.
Models And Estimation Of Genetic Effects
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Author : José M Álvarez-Castro
language : en
Publisher: Frontiers Media SA
Release Date : 2015-04-17
Models And Estimation Of Genetic Effects written by José M Álvarez-Castro and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-17 with Ecology categories.
Ronald Fisher needed to develop elaborate models of genetic effects in order to set the foundations of Quantitative Genetics in his 1918 paper “The correlation between relatives on the supposition of Mendelian inheritance”. Since then, many significant implementations have been made to model genetic effects. However, at the verge of one century after Fisher’s kick-off, models of genetic effects keep on being discussed and implemented. Indeed, the relatively recent advent of QTL analyses challenged the state of the art of this field by providing researchers the opportunity to obtain and analyze estimates of genetic effects from real data. In this context, the development of this field was not exempt of some polemics, like the debate about the convenience of the functional and the statistical epistasis approaches. This research topic is meant to provide recent developments in models and estimation of genetic effects and to enrich the discussion about how and why models of genetic effects must be further developed and applied. The articles in this Research Topic shall thus extend, refine and/or provide a refresh look at Fisher’s original models of genetic effects and their application to genetic effects estimation and to improve our understanding of evolutionary processes and breeding programs.