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Statistical Methods For High Dimensional Data In Genetic Epidemiology
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Book Synopsis High-dimensional Data Analysis by : Tony Cai;Xiaotong Shen
Download or read book High-dimensional Data Analysis written by Tony Cai;Xiaotong Shen and published by . This book was released on with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last few years, significant developments have been taking place in highdimensional data analysis, driven primarily by a wide range of applications in many fields such as genomics and signal processing. In particular, substantial advances have been made in the areas of feature selection, covariance estimation, classification and regression. This book intends to examine important issues arising from highdimensional data analysis to explore key ideas for statistical inference and prediction. It is structured around topics on multiple hypothesis testing, feature selection, regression, cla.
Book Synopsis An Introduction to Genetic Epidemiology by : Palmer, Lyle J.
Download or read book An Introduction to Genetic Epidemiology written by Palmer, Lyle J. and published by Policy Press. This book was released on 2011-05-31 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together leading experts to provide an introduction to genetic epidemiology that begins with a primer in human molecular genetics through all the standard methods in population genetics and genetic epidemiology required for an adequate grounding in the field.
Book Synopsis A Statistical Approach to Genetic Epidemiology by : Andreas Ziegler
Download or read book A Statistical Approach to Genetic Epidemiology written by Andreas Ziegler and published by John Wiley & Sons. This book was released on 2010-06-14 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diese zweite Auflage des sehr erfolgreichen Lehrbuchs der Statistik in der genetischen Epidemiologie wurde sorgfältig durchgesehen, aktualisiert und an vielen Stellen erweitert. Wie gewohnt mit vielen Aufgaben und Lösungen, dazu jetzt auch Farbabbildungen und auf Wunsch gekoppelt mit einem maßgeschneiderten E-Learning-Kurs.
Book Synopsis Biostatistics for Human Genetic Epidemiology by : Bertram K. C. Chan
Download or read book Biostatistics for Human Genetic Epidemiology written by Bertram K. C. Chan and published by Springer. This book was released on 2018-10-24 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solve problems in quantitative Genetic Epidemiology Biostatistics for Human Genetic Epidemiology provides statistical methodologies and R recipes for human genetic epidemiologic problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related human genetic epidemiology, with R codes illustrations for various examples. This clear and concise book covers human genetic epidemiology, using R in data analysis, including multivariate data analysis. It examines probabilistic and statistical theories for modeling human genetic epidemiology – leading the readers through an effective epidemiologic model, from simple to advanced levels. Classical mathematical, probabilistic, and statistical theory are thoroughly discussed and presented. This book also presents R as a calculator and using R in data analysis. Additionally, it covers Advanced Human Genetic Data Concepts, the Study of Human Genetic Variation, Manhattan Plots, as well as the Procedures for Multiple Comparison. Numerous Worked Examples are provided for illustrations of concepts and real-life applications. Biostatistics for Human Genetic Epidemiology is an ideal reference for professionals and students in Medicine (particularly in Preventive Medicine and Public Health Medical Practices), as well as in Genetics, Epidemiology, and Biostatistics.
Book Synopsis Handbook of Statistical Methods for Case-Control Studies by : Ørnulf Borgan
Download or read book Handbook of Statistical Methods for Case-Control Studies written by Ørnulf Borgan and published by CRC Press. This book was released on 2018-06-27 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistical Methods for Case-Control Studies is written by leading researchers in the field. It provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, as well as a review of classical principles and methods. The handbook is designed to serve as a reference text for biostatisticians and quantitatively-oriented epidemiologists who are working on the design and analysis of case-control studies or on related statistical methods research. Though not specifically intended as a textbook, it may also be used as a backup reference text for graduate level courses. Book Sections Classical designs and causal inference, measurement error, power, and small-sample inference Designs that use full-cohort information Time-to-event data Genetic epidemiology About the Editors Ørnulf Borgan is Professor of Statistics, University of Oslo. His book with Andersen, Gill and Keiding on counting processes in survival analysis is a world classic. Norman E. Breslow was, at the time of his death, Professor Emeritus in Biostatistics, University of Washington. For decades, his book with Nick Day has been the authoritative text on case-control methodology. Nilanjan Chatterjee is Bloomberg Distinguished Professor, Johns Hopkins University. He leads a broad research program in statistical methods for modern large scale biomedical studies. Mitchell H. Gail is a Senior Investigator at the National Cancer Institute. His research includes modeling absolute risk of disease, intervention trials, and statistical methods for epidemiology. Alastair Scott was, at the time of his death, Professor Emeritus of Statistics, University of Auckland. He was a major contributor to using survey sampling methods for analyzing case-control data. Chris J. Wild is Professor of Statistics, University of Auckland. His research includes nonlinear regression and methods for fitting models to response-selective data.
Book Synopsis Applied Statistical Genetics with R by : Andrea S. Foulkes
Download or read book Applied Statistical Genetics with R written by Andrea S. Foulkes and published by Springer Science & Business Media. This book was released on 2009-04-28 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical genetics has become a core course in many graduate programs in public health and medicine. This book presents fundamental concepts and principles in this emerging field at a level that is accessible to students and researchers with a first course in biostatistics. Extensive examples are provided using publicly available data and the open source, statistical computing environment, R.
Book Synopsis High-Dimensional Data Analysis in Cancer Research by : Xiaochun Li
Download or read book High-Dimensional Data Analysis in Cancer Research written by Xiaochun Li and published by Springer Science & Business Media. This book was released on 2008-12-19 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate analysis is a mainstay of statistical tools in the analysis of biomedical data. It concerns with associating data matrices of n rows by p columns, with rows representing samples (or patients) and columns attributes of samples, to some response variables, e.g., patients outcome. Classically, the sample size n is much larger than p, the number of variables. The properties of statistical models have been mostly discussed under the assumption of fixed p and infinite n. The advance of biological sciences and technologies has revolutionized the process of investigations of cancer. The biomedical data collection has become more automatic and more extensive. We are in the era of p as a large fraction of n, and even much larger than n. Take proteomics as an example. Although proteomic techniques have been researched and developed for many decades to identify proteins or peptides uniquely associated with a given disease state, until recently this has been mostly a laborious process, carried out one protein at a time. The advent of high throughput proteome-wide technologies such as liquid chromatography-tandem mass spectroscopy make it possible to generate proteomic signatures that facilitate rapid development of new strategies for proteomics-based detection of disease. This poses new challenges and calls for scalable solutions to the analysis of such high dimensional data. In this volume, we will present the systematic and analytical approaches and strategies from both biostatistics and bioinformatics to the analysis of correlated and high-dimensional data.
Book Synopsis Bioinformatics in Human Health and Heredity by : Ranajit Chakraborty
Download or read book Bioinformatics in Human Health and Heredity written by Ranajit Chakraborty and published by Newnes. This book was released on 2012-10-03 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. A series of handbooks is the only way of presenting the various aspects of statistical methodology, applications and developments. This volume deals with bioinformatics.
Book Synopsis Biostatistical Genetics and Genetic Epidemiology by : Robert C. Elston
Download or read book Biostatistical Genetics and Genetic Epidemiology written by Robert C. Elston and published by John Wiley & Sons. This book was released on 2002-04-22 with total page 860 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human Genetics concerns the study of genetic forces in man. By studying our genetic make-up we are able to understand more about our heritage and evolution. Some of the original, and most significant research in genetics centred around the study of the genetics of complex diseases - genetic epidemiology. This is the third in a highly successful series of books based on articles from the Encyclopedia of Biostatistics. This volume will be a timely and comprehensive reference, for a subject that has seen a recent explosion of interest following the completion of the first draft of the Human Genome Mapping Project. The editors have updated the articles from the Human Genetics section of the EoB, have adpated other articles to give them a genetic feel, and have included a number of newly commissioned articles to ensure the work is comprehensive and provides a self-contained reference.
Book Synopsis Application of Novel Statistical and Machine-learning Methods to High-dimensional Clinical Cancer and (Multi-)Omics data by : Chao Xu
Download or read book Application of Novel Statistical and Machine-learning Methods to High-dimensional Clinical Cancer and (Multi-)Omics data written by Chao Xu and published by Frontiers Media SA. This book was released on 2022-02-02 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Statistical Genetics by : David J. Balding
Download or read book Handbook of Statistical Genetics written by David J. Balding and published by John Wiley & Sons. This book was released on 2008-06-10 with total page 1616 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook for Statistical Genetics is widely regarded as the reference work in the field. However, the field has developed considerably over the past three years. In particular the modeling of genetic networks has advanced considerably via the evolution of microarray analysis. As a consequence the 3rd edition of the handbook contains a much expanded section on Network Modeling, including 5 new chapters covering metabolic networks, graphical modeling and inference and simulation of pedigrees and genealogies. Other chapters new to the 3rd edition include Human Population Genetics, Genome-wide Association Studies, Family-based Association Studies, Pharmacogenetics, Epigenetics, Ethic and Insurance. As with the second Edition, the Handbook includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between the chapters, tying the different areas together. With heavy use of up-to-date examples, real-life case studies and references to web-based resources, this continues to be must-have reference in a vital area of research. Edited by the leading international authorities in the field. David Balding - Department of Epidemiology & Public Health, Imperial College An advisor for our Probability & Statistics series, Professor Balding is also a previous Wiley author, having written Weight-of-Evidence for Forensic DNA Profiles, as well as having edited the two previous editions of HSG. With over 20 years teaching experience, he’s also had dozens of articles published in numerous international journals. Martin Bishop – Head of the Bioinformatics Division at the HGMP Resource Centre As well as the first two editions of HSG, Dr Bishop has edited a number of introductory books on the application of informatics to molecular biology and genetics. He is the Associate Editor of the journal Bioinformatics and Managing Editor of Briefings in Bioinformatics. Chris Cannings – Division of Genomic Medicine, University of Sheffield With over 40 years teaching in the area, Professor Cannings has published over 100 papers and is on the editorial board of many related journals. Co-editor of the two previous editions of HSG, he also authored a book on this topic.
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 Handbook of Statistical Genomics by : David J. Balding
Download or read book Handbook of Statistical Genomics written by David J. Balding and published by John Wiley & Sons. This book was released on 2019-07-02 with total page 1219 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Clinical Trial Biostatistics and Biopharmaceutical Applications by : Walter R. Young
Download or read book Clinical Trial Biostatistics and Biopharmaceutical Applications written by Walter R. Young and published by CRC Press. This book was released on 2014-11-20 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since 1945, "The Annual Deming Conference on Applied Statistics" has been an important event in the statistics profession. In Clinical Trial Biostatistics and Biopharmaceutical Applications, prominent speakers from past Deming conferences present novel biostatistical methodologies in clinical trials as well as up-to-date biostatistical applications from the pharmaceutical industry. Divided into five sections, the book begins with emerging issues in clinical trial design and analysis, including the roles of modeling and simulation, the pros and cons of randomization procedures, the design of Phase II dose-ranging trials, thorough QT/QTc clinical trials, and assay sensitivity and the constancy assumption in noninferiority trials. The second section examines adaptive designs in drug development, discusses the consequences of group-sequential and adaptive designs, and illustrates group sequential design in R. The third section focuses on oncology clinical trials, covering competing risks, escalation with overdose control (EWOC) dose finding, and interval-censored time-to-event data. In the fourth section, the book describes multiple test problems with applications to adaptive designs, graphical approaches to multiple testing, the estimation of simultaneous confidence intervals for multiple comparisons, and weighted parametric multiple testing methods. The final section discusses the statistical analysis of biomarkers from omics technologies, biomarker strategies applicable to clinical development, and the statistical evaluation of surrogate endpoints. This book clarifies important issues when designing and analyzing clinical trials, including several misunderstood and unresolved challenges. It will help readers choose the right method for their biostatistical application. Each chapter is self-contained with references.
Book Synopsis Integrating Omics Data by : George Tseng
Download or read book Integrating Omics Data written by George Tseng and published by Cambridge University Press. This book was released on 2015-09-23 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: In most modern biomedical research projects, application of high-throughput genomic, proteomic, and transcriptomic experiments has gradually become an inevitable component. Popular technologies include microarray, next generation sequencing, mass spectrometry and proteomics assays. As the technologies have become mature and the price affordable, omics data are rapidly generated, and the problem of information integration and modeling of multi-lab and/or multi-omics data is becoming a growing one in the bioinformatics field. This book provides comprehensive coverage of these topics and will have a long-lasting impact on this evolving subject. Each chapter, written by a leader in the field, introduces state-of-the-art methods to handle information integration, experimental data, and database problems of omics data.
Book Synopsis Statistical Approaches to Gene x Environment Interactions for Complex Phenotypes by : Michael Windle
Download or read book Statistical Approaches to Gene x Environment Interactions for Complex Phenotypes written by Michael Windle and published by MIT Press. This book was released on 2016-07-08 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diverse methodological and statistical approaches for investigating the role of gene-environment interactions in a range of complex diseases and traits. Findings from the Human Genome Project and from Genome-Wide Association (GWA) studies indicate that many diseases and traits manifest a more complex genomic pattern than previously assumed. These findings, and advances in high-throughput sequencing, suggest that there are many sources of influence—genetic, epigenetic, and environmental. This volume investigates the role of the interactions of genes and environment (G × E) in diseases and traits (referred to by the contributors as complex phenotypes) including depression, diabetes, obesity, and substance use. The contributors first present different statistical approaches or strategies to address G × E and G × G interactions with high-throughput sequenced data, including two-stage procedures to identify G × E and G × G interactions, marker-set approaches to assessing interactions at the gene level, and the use of a partial-least square (PLS) approach. The contributors then turn to specific complex phenotypes, research designs, or combined methods that may advance the study of G × E interactions, considering such topics as randomized clinical trials in obesity research, longitudinal research designs and statistical models, and the development of polygenic scores to investigate G × E interactions. Contributors Fatima Umber Ahmed, Yin-Hsiu Chen, James Y. Dai, Caroline Y. Doyle, Zihuai He, Li Hsu, Shuo Jiao, Erin Loraine Kinnally, Yi-An Ko, Charles Kooperberg, Seunggeun Lee, Arnab Maity, Jeanne M. McCaffery, Bhramar Mukherjee, Sung Kyun Park, Duncan C. Thomas, Alexandre Todorov, Jung-Ying Tzeng, Tao Wang, Michael Windle, Min Zhang
Book Synopsis Bioinformatics Methods by : Shili Lin
Download or read book Bioinformatics Methods written by Shili Lin and published by CRC Press. This book was released on 2022-09-16 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past three decades have witnessed an explosion of what is now referred to as high-dimensional `omics' data. Bioinformatics Methods: From Omics to Next Generation Sequencing describes the statistical methods and analytic frameworks that are best equipped to interpret these complex data and how they apply to health-related research. Covering the technologies that generate data, subtleties of various data types, and statistical underpinnings of methods, this book identifies a suite of potential analytic tools, and highlights commonalities among statistical methods that have been developed. An ideal reference for biostatisticians and data analysts that work in collaboration with scientists and clinical investigators looking to ensure rigorous application of available methodologies. Key Features: Survey of a variety of omics data types and their unique features Summary of statistical underpinnings for widely used omics data analysis methods Description of software resources for performing omics data analyses
