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Microarrays Empirical Bayes And The Two Groups Model
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Book Synopsis A Mixture Model Approach to Empirical Bayes Testing and Estimation by : Omkar Muralidharan
Download or read book A Mixture Model Approach to Empirical Bayes Testing and Estimation written by Omkar Muralidharan and published by Stanford University. This book was released on 2011 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many modern statistical problems require making similar decisions or estimates for many different entities. For example, we may ask whether each of 10,000 genes is associated with some disease, or try to measure the degree to which each is associated with the disease. As in this example, the entities can often be divided into a vast majority of "null" objects and a small minority of interesting ones. Empirical Bayes is a useful technique for such situations, but finding the right empirical Bayes method for each problem can be difficult. Mixture models, however, provide an easy and effective way to apply empirical Bayes. This thesis motivates mixture models by analyzing a simple high-dimensional problem, and shows their practical use by applying them to detecting single nucleotide polymorphisms.
Book Synopsis Large-Scale Inference by : Bradley Efron
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.
Book Synopsis The Analysis of Gene Expression Data by : Giovanni Parmigiani
Download or read book The Analysis of Gene Expression Data written by Giovanni Parmigiani and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.
Book Synopsis Statistical Bioinformatics with R by : Sunil K. Mathur
Download or read book Statistical Bioinformatics with R written by Sunil K. Mathur and published by Academic Press. This book was released on 2009-12-21 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications. Designed for a one or two semester senior undergraduate or graduate bioinformatics course, the text takes a broad view of the subject – not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications. The inclusion of R & SAS code as well as the development of advanced methodology such as Bayesian and Markov models provides students with the important foundation needed to conduct bioinformatics. - Integrates biological, statistical and computational concepts - Inclusion of R & SAS code - Provides coverage of complex statistical methods in context with applications in bioinformatics - Exercises and examples aid teaching and learning presented at the right level - Bayesian methods and the modern multiple testing principles in one convenient book
Book Synopsis Resampling-Based Multiple Testing by : Peter H. Westfall
Download or read book Resampling-Based Multiple Testing written by Peter H. Westfall and published by John Wiley & Sons. This book was released on 1993-01-12 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power.
Book Synopsis Handbook of Multiple Comparisons by : Xinping Cui
Download or read book Handbook of Multiple Comparisons written by Xinping Cui and published by CRC Press. This book was released on 2021-11-18 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparison problems big and small, with guidance toward error rate control and insights on how principles developed earlier can be applied to current and emerging problems. Some highlights of the coverages are as follows. Error rate control is useful for controlling the incorrect decision rate. Chapter 1 introduces Tukey's original multiple comparison error rates and point to how they have been applied and adapted to modern multiple comparison problems as discussed in the later chapters. Principles endure. While the closed testing principle is more familiar, Chapter 4 shows the partitioning principle can derive confidence sets for multiple tests, which may become important as the profession goes beyond making decisions based on p-values. Multiple comparisons of treatment efficacy often involve multiple doses and endpoints. Chapter 12 on multiple endpoints explains how different choices of endpoint types lead to different multiplicity adjustment strategies, while Chapter 11 on the MCP-Mod approach is particularly useful for dose-finding. To assess efficacy in clinical trials with multiple doses and multiple endpoints, the reader can see the traditional approach in Chapter 2, the Graphical approach in Chapter 5, and the multivariate approach in Chapter 3. Personalized/precision medicine based on targeted therapies, already a reality, naturally leads to analysis of efficacy in subgroups. Chapter 13 draws attention to subtle logical issues in inferences on subgroups and their mixtures, with a principled solution that resolves these issues. This chapter has implication toward meeting the ICHE9R1 Estimands requirement. Besides the mere multiple testing methodology itself, the handbook also covers related topics like the statistical task of model selection in Chapter 7 or the estimation of the proportion of true null hypotheses (or, in other words, the signal prevalence) in Chapter 8. It also contains decision-theoretic considerations regarding the admissibility of multiple tests in Chapter 6. The issue of selected inference is addressed in Chapter 9. Comparison of responses can involve millions of voxels in medical imaging or SNPs in genome-wide association studies (GWAS). Chapter 14 and Chapter 15 provide state of the art methods for large scale simultaneous inference in these settings.
Book Synopsis Phenotypes and Genotypes by : Florian Frommlet
Download or read book Phenotypes and Genotypes written by Florian Frommlet and published by Springer. This book was released on 2016-02-12 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Handbook of Statistical Systems Biology by : Michael Stumpf
Download or read book Handbook of Statistical Systems Biology written by Michael Stumpf and published by John Wiley & Sons. This book was released on 2011-09-09 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book: Provides a comprehensive account of inference techniques in systems biology. Introduces classical and Bayesian statistical methods for complex systems. Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems. Discusses various applications for statistical systems biology, such as gene regulation and signal transduction. Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies. Presents an in-depth presentation of reverse engineering approaches. Provides colour illustrations to explain key concepts. This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.
Book Synopsis The Theory That Would Not Die by : Sharon Bertsch McGrayne
Download or read book The Theory That Would Not Die written by Sharon Bertsch McGrayne and published by Yale University Press. This book was released on 2011-05-17 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This account of how a once reviled theory, Baye’s rule, came to underpin modern life is both approachable and engrossing" (Sunday Times). A New York Times Book Review Editors’ Choice Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the generations-long human drama surrounding it. McGrayne traces the rule’s discovery by an 18th century amateur mathematician through its development by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—while practitioners relied on it to solve crises involving great uncertainty and scanty information, such as Alan Turing's work breaking Germany's Enigma code during World War II. McGrayne also explains how the advent of computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security. Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.
Book Synopsis Mathematical Statistics by : Peter J. Bickel
Download or read book Mathematical Statistics written by Peter J. Bickel and published by CRC Press. This book was released on 2015-11-04 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Statistics: Basic Ideas and Selected Topics, Volume II presents important statistical concepts, methods, and tools not covered in the authors' previous volume. This second volume focuses on inference in non- and semiparametric models. It not only reexamines the procedures introduced in the first volume from a more sophisticated point o
Book Synopsis Bayesian and Frequentist Regression Methods by : Jon Wakefield
Download or read book Bayesian and Frequentist Regression Methods written by Jon Wakefield and published by Springer Science & Business Media. This book was released on 2013-01-04 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place. The two philosophical approaches to regression methodology are featured here as complementary techniques, with theory and data analysis providing supplementary components of the discussion. In particular, methods are illustrated using a variety of data sets. The majority of the data sets are drawn from biostatistics but the techniques are generalizable to a wide range of other disciplines.
Book Synopsis Bioinformatics and Computational Biology Solutions Using R and Bioconductor by : Robert Gentleman
Download or read book Bioinformatics and Computational Biology Solutions Using R and Bioconductor written by Robert Gentleman and published by Springer Science & Business Media. This book was released on 2005-12-29 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
Book Synopsis Stochastic Processes in Genetics and Evolution by : Charles J. Mode
Download or read book Stochastic Processes in Genetics and Evolution written by Charles J. Mode and published by World Scientific. This book was released on 2012 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of this book is the field of evolutionary genetics. The book contains new methods for simulating evolution at the genomic level. It sets out applications using up to date Monte Carlo simulation methods applied in classical population genetics, and sets out new fields of quantifying mutation and selection at the Mendelian level. A serious limitation of Wright-Fisher process, the assumption that population size is constant, motivated the introduction of self regulating branching processes in this book. While providing a short review of the principles of probability and its application and using computer intensive methods whilst applying these principles, this book explains how it is possible to derive new formulas expressed in terms of matrix algebra providing new insights into the classical Wright-Fisher processes of evolutionary genetics. Also covered are the development of new methods for studying genetics and evolution, simulating nucleotide substitutions of a DNA molecule and on self regulating branching processes. Components of natural selection are studied in terms of reproductive success of each genotype whilst also studying the differential ability of genotypes to compete for resources and sexual selection. The concept of the gene is also reviewed in this book, and it provides a current definition of a gene based on very recent experiments with micro-array technologies. A development of stochastic models for simulating the evolution of model genomes concludes the studies in this book. Deserving of a place on the book shelves of workers in biomathematics, applied probability, stochastic processes and statistics, as well as in bioinformatics and phylogenetics, it will also be relevant to those interested in computer simulation, and evolutionary biologists interested in quantitative methods.
Download or read book Inferential Models written by Ryan Martin and published by CRC Press. This book was released on 2015-09-25 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: A New Approach to Sound Statistical ReasoningInferential Models: Reasoning with Uncertainty introduces the authors' recently developed approach to inference: the inferential model (IM) framework. This logical framework for exact probabilistic inference does not require the user to input prior information. The authors show how an IM produces meaning
Book Synopsis Bayesian Statistics 9 by : José M. Bernardo
Download or read book Bayesian Statistics 9 written by José M. Bernardo and published by Oxford University Press. This book was released on 2011-10-06 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian statistics is a dynamic and fast-growing area of statistical research and the Valencia International Meetings provide the main forum for discussion. These resulting proceedings form an up-to-date collection of research.
Book Synopsis Handbook of Big Data Analytics by : Wolfgang Karl Härdle
Download or read book Handbook of Big Data Analytics written by Wolfgang Karl Härdle and published by Springer. This book was released on 2018-07-20 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Book Synopsis Likelihood Methods in Biology and Ecology by : Michael Brimacombe
Download or read book Likelihood Methods in Biology and Ecology written by Michael Brimacombe and published by CRC Press. This book was released on 2018-12-18 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book emphasizes the importance of the likelihood function in statistical theory and applications and discusses it in the context of biology and ecology. Bayesian and frequentist methods both use the likelihood function and provide differing but related insights. This is examined here both through review of basic methodology and also the integr
