Download or read book MULTIPLE TESTING CORRECTION IN TIME SERIES ROLLING WINDOW ANALYSIS WITH APPLICATION OF GWAS METHODS written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : Rolling window is a popular tool in time series analysis. When conducting hypothesis testing on each window simultaneously, multiple testing problem occurs. In the literature in rolling window analysis, it appears that bootstrap is the most frequently used, if not only, method to address the multiple testing issue. This thesis aims to adapt multiple testing correction methods that are popular in genome-wide association study to the time series rolling window context. In particular, some of these methods require the knowledge of the correlation structure of test statistics. In genetics, this structure can be obtained from an external source, which may not exist in time series. To overcome this difficulty, we adopt the AR sieve idea, which enables the computation of correlation structure based on the estimated AR coefficients. We also present the finite sample simulation to illustrate the performance of these methods.

Download or read book Robust Computational Tools for Multiple Testing with Genetic Association Studies written by William L. Welbourn (Jr.) and published by . This book was released on 2012 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resolving the interplay of the genetic components of a complex disease is a challenging endeavor. Over the past several years, genome-wide association studies (GWAS) have emerged as a popular approach at locating common genetic variation within the human genome associated with disease risk. Assessing genetic-phenotype associations upon hundreds of thousands of genetic markers using the GWAS approach, introduces the potentially high number of false positive signals and requires statistical correction for multiple hypothesis testing. Permutation tests are considered the gold standard for multiple testing correction in GWAS, because they simultaneously provide unbiased Type I error control and high power. However, they demand heavy computational effort, especially with large-scale data sets of modern GWAS. In recent years, the computational problem has been circumvented by using approximations to permutation tests, but several studies have posed sampling conditions in which these approximations are suggestive to be biased. We have developed an optimized parallel algorithm for the permutation testing approach to multiple testing correction in GWAS, whose implementation essentially abates the computational problem. When introduced to GWAS data, our algorithm yields rapid, precise, and powerful multiplicity adjustment, many orders of magnitude faster than existing employed GWAS statistical software. Although GWAS have identified many potentially important genetic associations which will advance our understanding of human disease, the common variants with modest effects on disease risk discovered through this approach likely account for a small proportion of the heritability in complex disease. On the other hand, interactions between genetic and environmental factors could account for a substantial proportion of the heritability in a complex disease and are overlooked within the GWAS approach. We have developed an efficient and easily implemented tool for genetic association studies, whose aim is identifying genes involved in a gene-environment interaction. Our approach is amenable to a wide range of association studies and assorted densities in sampled genetic marker panels, and incorporates resampling for multiple testing correction. Within the context of a case-control study design we demonstrate by way of simulation that our proposed method offers greater statistical power to detect gene-environment interaction, when compared to several competing approaches to assess this type of interaction.

Download or read book Design of Efficient and Accurate Statistical Approaches to Correct for Confounding Effects and Identify True Signals in Genetic Association Studies written by JONG WHA JOANNE JOO and published by . This book was released on 2015 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decades, genome-wide association studies have dramatically improved especially with the advent of the hight-throughput technologies such as microarray and next generation sequencing. Although genome-wide association studies have been extremely successful in identifying tens of thousands of variants associated with various disease or traits, many studies have reported that some of the associations are spurious induced by various confounding factors such as population structure or technical artifacts. In this dissertation, I focus on effectively and accurately identifying true signals in genome-wide association studies in the presence of confounding effects. First, I introduce a method that effectively identifying regulatory hotspots while correcting for false signals induced by technical confounding effects in expression quantitative loci studies. Technical confounding factors such as a batch effect complicates the expression quantitative loci analysis by inducing heterogeneity in gene expressions. This creates correlations between the samples and may cause spurious associations leading to spurious regulatory hotspots. By formulating the problem of identifying genetic signals in a linear mixed model framework, I show how we can identify regulatory hotspots while capturing heterogeneity in expression quantitative loci studies. Second, I introduce an efficient and accurate multiple-phenotype analysis method for high-dimensional data in the presence of population structure. Recently, large amounts of genomic data such as expression data have been collected from genome-wide association studies cohorts and in many cases it is preferable to analyze more than thousands of phenotypes simultaneously than analyze each phenotype one at a time. However, when confounding factors, such as population structure, exit in the data, even a small bias is induced by the confounding effects, the bias accumulates for each phenotype and may cause serious problems in multiple-phenotype analysis. By incorporating linear mixed model in the statistics of multivariate regression, I show we can increase the accuracy of multiple phenotype analysis dramatically in high- dimensional data. Lastly, I introduce an efficient multiple testing correction method in linear mixed model. The significance threshold differs as a function of species, marker densities, genetic relatedness, and trait heritability. However, none of the previous multiple testing correction methods can comprehensively account for these factors. I show that the significant threshold changes with the dosage of genetic relatedness and introduce a novel multiple testing correction approach that utilizes linear mixed model to account for the confounding effects in the data.

Download or read book Association Mapping in Plants written by Nnadozie C. Oraguzie and published by Springer Science & Business Media. This book was released on 2007-01-06 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides both basic and advanced understanding of association mapping and an awareness of population genomics tools to facilitate mapping and identification of the underlying causes of quantitative trait variation in plants. It acts as a useful review of the marker technology, the statistical methodology, and the progress to date. It also offers guides to the use of single nucleotide polymorphisms (SNPs) in association studies.

Download or read book Seamless R and C Integration with Rcpp written by Dirk Eddelbuettel and published by Springer Science & Business Media. This book was released on 2013-06-04 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rcpp is the glue that binds the power and versatility of R with the speed and efficiency of C++. With Rcpp, the transfer of data between R and C++ is nearly seamless, and high-performance statistical computing is finally accessible to most R users. Rcpp should be part of every statistician's toolbox. -- Michael Braun, MIT Sloan School of Management "Seamless R and C++ integration with Rcpp" is simply a wonderful book. For anyone who uses C/C++ and R, it is an indispensable resource. The writing is outstanding. A huge bonus is the section on applications. This section covers the matrix packages Armadillo and Eigen and the GNU Scientific Library as well as RInside which enables you to use R inside C++. These applications are what most of us need to know to really do scientific programming with R and C++. I love this book. -- Robert McCulloch, University of Chicago Booth School of Business Rcpp is now considered an essential package for anybody doing serious computational research using R. Dirk's book is an excellent companion and takes the reader from a gentle introduction to more advanced applications via numerous examples and efficiency enhancing gems. The book is packed with all you might have ever wanted to know about Rcpp, its cousins (RcppArmadillo, RcppEigen .etc.), modules, package development and sugar. Overall, this book is a must-have on your shelf. -- Sanjog Misra, UCLA Anderson School of Management The Rcpp package represents a major leap forward for scientific computations with R. With very few lines of C++ code, one has R's data structures readily at hand for further computations in C++. Hence, high-level numerical programming can be made in C++ almost as easily as in R, but often with a substantial speed gain. Dirk is a crucial person in these developments, and his book takes the reader from the first fragile steps on to using the full Rcpp machinery. A very recommended book! -- Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark "Seamless R and C ++ Integration with Rcpp" provides the first comprehensive introduction to Rcpp. Rcpp has become the most widely-used language extension for R, and is deployed by over one-hundred different CRAN and BioConductor packages. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease. This brings the depth of the R analysis framework together with the power, speed, and efficiency of C++. Dirk Eddelbuettel has been a contributor to CRAN for over a decade and maintains around twenty packages. He is the Debian/Ubuntu maintainer for R and other quantitative software, edits the CRAN Task Views for Finance and High-Performance Computing, is a co-founder of the annual R/Finance conference, and an editor of the Journal of Statistical Software. He holds a Ph.D. in Mathematical Economics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.

Download or read book Genomics Assisted Crop Improvement written by R.K. Varshney and published by Springer Science & Business Media. This book was released on 2007-12-12 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This superb volume provides a critical assessment of genomics tools and approaches for crop breeding. Volume 1 presents the status and availability of genomic resources and platforms, and also devises strategies and approaches for effectively exploiting genomics research. Volume 2 goes into detail on a number of case studies of several important crop and plant species that summarize both the achievements and limitations of genomics research for crop improvement.

Download or read book Craniofacial Development The Tissue and Molecular Interactions That Control Development of the Head written by Philippa H. Francis-West and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Craniofacial development is a multistep and intricate process initially involving a number of inductive interactions that control neural and neural crest development, which are followed by a series of epithelial-mesenchymal interactions that control outgrowth, patterning, and skeletal differentiation. Certain aspects of craniofacial development are unique developmental processes in higher vertebrates. First, in higher vertebrates the cranial neural crest, in contrast to the trunk neural crest, gives rise to the skeletal structures. These skeletal elements include those comprising mem brane bone and secondary cartilage, which with the exception of the clavicle are tissue types found exclusively in the head in higher vertebrates. Second, with the exception of the tongue, the origin of the musculature is distinct from other regions of the body. The body and tongue muscles are formed from the segmented epithelial somites whilst the head musculature is formed from unsegmented paraxial and prechordal mesoderm. Furthermore, the signalling cascades that control myogenic differentia tion appear to be distinct as determined by gene expression and the response of myogenic cells to growth factors. Finally, the neurogenic placodes, which give rise to the sensory organs and some cranial ganglia, are only found in the head. Over recent years, there have been significant advances in our knowledge of the molecular proc esses that control craniofacial development in a number of animal models. This has given insight into the genes that control many aspects of head development from the initial induction of the head to the final stages of differentiation.

Download or read book Genome Wide Association Studies and Genomic Prediction written by Cedric Gondro and published by Humana Press. This book was released on 2013-06-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the detailed genomic information that is now becoming available, we have a plethora of data that allows researchers to address questions in a variety of areas. Genome-wide association studies (GWAS) have become a vital approach to identify candidate regions associated with complex diseases in human medicine, production traits in agriculture, and variation in wild populations. Genomic prediction goes a step further, attempting to predict phenotypic variation in these traits from genomic information. Genome-Wide Association Studies and Genomic Prediction pulls together expert contributions to address this important area of study. The volume begins with a section covering the phenotypes of interest as well as design issues for GWAS, then moves on to discuss efficient computational methods to store and handle large datasets, quality control measures, phasing, haplotype inference, and imputation. Later chapters deal with statistical approaches to data analysis where the experimental objective is either to confirm the biology by identifying genomic regions associated to a trait or to use the data to make genomic predictions about a future phenotypic outcome (e.g. predict onset of disease). As part of the Methods in Molecular Biology series, chapters provide helpful, real-world implementation advice.

Download or read book Machine Learning in Radiation Oncology written by Issam El Naqa and published by Springer. This book was released on 2015-06-19 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

Download or read book Genomics of Plant Genetic Resources written by Roberto Tuberosa and published by Springer Science & Business Media. This book was released on 2013-11-08 with total page 711 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our lives and well being intimately depend on the exploitation of the plant genetic resources available to our breeding programs. Therefore, more extensive exploration and effective exploitation of plant genetic resources are essential prerequisites for the release of improved cultivars. Accordingly, the remarkable progress in genomics approaches and more recently in sequencing and bioinformatics offers unprecedented opportunities for mining germplasm collections, mapping and cloning loci of interest, identifying novel alleles and deploying them for breeding purposes. This book collects 48 highly interdisciplinary articles describing how genomics improves our capacity to characterize and harness natural and artificially induced variation in order to boost crop productivity and provide consumers with high-quality food. This book will be an invaluable reference for all those interested in managing, mining and harnessing the genetic richness of plant genetic resources.

Download or read book Genome Data Analysis written by Ju Han Kim and published by Springer. This book was released on 2019-04-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.

Download or read book Human Genetics and Genomics written by Bruce R. Korf and published by John Wiley & Sons. This book was released on 2012-11-19 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fourth edition of the best-selling textbook, Human Genetics and Genomics, clearly explains the key principles needed by medical and health sciences students, from the basis of molecular genetics, to clinical applications used in the treatment of both rare and common conditions. A newly expanded Part 1, Basic Principles of Human Genetics, focuses on introducing the reader to key concepts such as Mendelian principles, DNA replication and gene expression. Part 2, Genetics and Genomics in Medical Practice, uses case scenarios to help you engage with current genetic practice. Now featuring full-color diagrams, Human Genetics and Genomics has been rigorously updated to reflect today’s genetics teaching, and includes updated discussion of genetic risk assessment, “single gene” disorders and therapeutics. Key learning features include: Clinical snapshots to help relate science to practice 'Hot topics' boxes that focus on the latest developments in testing, assessment and treatment 'Ethical issues' boxes to prompt further thought and discussion on the implications of genetic developments 'Sources of information' boxes to assist with the practicalities of clinical research and information provision Self-assessment review questions in each chapter Accompanied by the Wiley E-Text digital edition (included in the price of the book), Human Genetics and Genomics is also fully supported by a suite of online resources at www.korfgenetics.com, including: Factsheets on 100 genetic disorders, ideal for study and exam preparation Interactive Multiple Choice Questions (MCQs) with feedback on all answers Links to online resources for further study Figures from the book available as PowerPoint slides, ideal for teaching purposes The perfect companion to the genetics component of both problem-based learning and integrated medical courses, Human Genetics and Genomics presents the ideal balance between the bio-molecular basis of genetics and clinical cases, and provides an invaluable overview for anyone wishing to engage with this fast-moving discipline.

Download or read book Computational Toxicology written by Orazio Nicolotti and published by Springer Nature. This book was released on with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book R in Action written by Robert Kabacoff and published by Manning Publications. This book was released on 2015-03-03 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data. R in Action, Second Edition is a language tutorial focused on practical problems. Written by a research methodologist, it takes a direct and modular approach to quickly give readers the information they need to produce useful results. Focusing on realistic data analyses and a comprehensive integration of graphics, it follows the steps that real data analysts use to acquire their data, get it into shape, analyze it, and produce meaningful results that they can provide to clients. Purchase of the print book comes with an offer of a free PDF eBook from Manning. Also available is all code from the book.

Download or read book Large Scale Inference written by Bradley Efron and published by Cambridge University Press. This book was released on 2012-11-29 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.

Download or read book Mendelian Randomization written by Stephen Burgess and published by CRC Press. This book was released on 2015-03-06 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the Terminology and Methods of Mendelian Randomization for Epidemiological StudiesMendelian randomization uses genetic instrumental variables to make inferences about causal effects based on observational data. It, therefore, can be a reliable way of assessing the causal nature of risk factors, such as biomarkers, for a wide range of disea

Download or read book Principles of Nutrigenetics and Nutrigenomics written by Raffaele De Caterina and published by Academic Press. This book was released on 2019-09-22 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Nutrigenetics and Nutrigenomics: Fundamentals for Individualized Nutrition is the most comprehensive foundational text on the complex topics of nutrigenetics and nutrigenomics. Edited by three leaders in the field with contributions from the most well-cited researchers conducting groundbreaking research in the field, the book covers how the genetic makeup influences the response to foods and nutrients and how nutrients affect gene expression. Principles of Nutrigenetics and Nutrigenomics: Fundamentals for Individualized Nutrition is broken into four parts providing a valuable overview of genetics, nutrigenetics, and nutrigenomics, and a conclusion that helps to translate research into practice. With an overview of the background, evidence, challenges, and opportunities in the field, readers will come away with a strong understanding of how this new science is the frontier of medical nutrition. Principles of Nutrigenetics and Nutrigenomics: Fundamentals for Individualized Nutrition is a valuable reference for students and researchers studying nutrition, genetics, medicine, and related fields. - Uniquely foundational, comprehensive, and systematic approach with full evidence-based coverage of established and emerging topics in nutrigenetics and nutrigenomics - Includes a valuable guide to ethics for genetic testing for nutritional advice - Chapters include definitions, methods, summaries, figures, and tables to help students, researchers, and faculty grasp key concepts - Companion website includes slide decks, images, questions, and other teaching and learning aids designed to facilitate communication and comprehension of the content presented in the book