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Primer To Analysis Of Genomic Data Using R

Author : Cedric Gondro
ISBN : 9783319144757
Genre : Medical
File Size : 43.75 MB
Format : PDF, ePub
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Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps. The philosophy behind the book is to start with real world raw datasets and perform all the analytical steps needed to reach final results. Though theory plays an important role, this is a practical book for graduate and undergraduate courses in bioinformatics and genomic analysis or for use in lab sessions. How to handle and manage high-throughput genomic data, create automated workflows and speed up analyses in R is also taught. A wide range of R packages useful for working with genomic data are illustrated with practical examples. The key topics covered are association studies, genomic prediction, estimation of population genetic parameters and diversity, gene expression analysis, functional annotation of results using publically available databases and how to work efficiently in R with large genomic datasets. Important principles are demonstrated and illustrated through engaging examples which invite the reader to work with the provided datasets. Some methods that are discussed in this volume include: signatures of selection, population parameters (LD, FST, FIS, etc); use of a genomic relationship matrix for population diversity studies; use of SNP data for parentage testing; snpBLUP and gBLUP for genomic prediction. Step-by-step, all the R code required for a genome-wide association study is shown: starting from raw SNP data, how to build databases to handle and manage the data, quality control and filtering measures, association testing and evaluation of results, through to identification and functional annotation of candidate genes. Similarly, gene expression analyses are shown using microarray and RNAseq data. At a time when genomic data is decidedly big, the skills from this book are critical. In recent years R has become the de facto tool for analysis of gene expression data, in addition to its prominent role in analysis of genomic data. Benefits to using R include the integrated development environment for analysis, flexibility and control of the analytic workflow. Included topics are core components of advanced undergraduate and graduate classes in bioinformatics, genomics and statistical genetics. This book is also designed to be used by students in computer science and statistics who want to learn the practical aspects of genomic analysis without delving into algorithmic details. The datasets used throughout the book may be downloaded from the publisher’s website./p
Category: Medical

Applied Survival Analysis Using R

Author : Dirk F. Moore
ISBN : 9783319312453
Genre : Medical
File Size : 64.38 MB
Format : PDF, Kindle
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Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.
Category: Medical

Bayesian Cost Effectiveness Analysis With The R Package Bcea

Author : Gianluca Baio
ISBN : 9783319557182
Genre : Medical
File Size : 53.7 MB
Format : PDF, Docs
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The book provides a description of the process of health economic evaluation and modelling for cost-effectiveness analysis, particularly from the perspective of a Bayesian statistical approach. Some relevant theory and introductory concepts are presented using practical examples and two running case studies. The book also describes in detail how to perform health economic evaluations using the R package BCEA (Bayesian Cost-Effectiveness Analysis). BCEA can be used to post-process the results of a Bayesian cost-effectiveness model and perform advanced analyses producing standardised and highly customisable outputs. It presents all the features of the package, including its many functions and their practical application, as well as its user-friendly web interface. The book is a valuable resource for statisticians and practitioners working in the field of health economics wanting to simplify and standardise their workflow, for example in the preparation of dossiers in support of marketing authorisation, or academic and scientific publications.
Category: Medical

Heart Rate Variability Analysis With The R Package Rhrv

Author : Constantino Antonio García Martínez
ISBN : 9783319653556
Genre : Medical
File Size : 74.27 MB
Format : PDF
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This book introduces readers to the basic concepts of Heart Rate Variability (HRV) and its most important analysis algorithms using a hands-on approach based on the open-source RHRV software. HRV refers to the variation over time of the intervals between consecutive heartbeats. Despite its apparent simplicity, HRV is one of the most important markers of the autonomic nervous system activity and it has been recognized as a useful predictor of several pathologies. The book discusses all the basic HRV topics, including the physiological contributions to HRV, clinical applications, HRV data acquisition, HRV data manipulation and HRV analysis using time-domain, frequency-domain, time-frequency, nonlinear and fractal techniques. Detailed examples based on real data sets are provided throughout the book to illustrate the algorithms and discuss the physiological implications of the results. Offering a comprehensive guide to analyzing beat information with RHRV, the book is intended for masters and Ph.D. students in various disciplines such as biomedical engineering, human and veterinary medicine, biology, and pharmacy, as well as researchers conducting heart rate variability analyses on both human and animal data.
Category: Medical

Data Wrangling With R

Author : Bradley Boehmke
ISBN : 9783319455990
Genre : Computers
File Size : 50.38 MB
Format : PDF, ePub
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This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques. This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned: How to work with different types of data such as numerics, characters, regular expressions, factors, and dates The difference between different data structures and how to create, add additional components to, and subset each data structure How to acquire and parse data from locations previously inaccessible How to develop functions and use loop control structures to reduce code redundancy How to use pipe operators to simplify code and make it more readable How to reshape the layout of data and manipulate, summarize, and join data sets
Category: Computers

A Primer In Biological Data Analysis And Visualization Using R

Author : Gregg Hartvigsen
ISBN : 9780231537049
Genre : Science
File Size : 85.34 MB
Format : PDF, Kindle
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R is a popular programming language that statisticians use to perform a variety of statistical computing tasks. Rooted in Gregg Hartvigsen's extensive experience teaching biology, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio to the organization, computation, and visualization of biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to express data in histograms, boxplots, barplots, scatterplots, before/after line plots, pie charts, and graphs. He covers data normality, outliers, and nonnormal data and examines frequently used statistical tests with one value and one sample; paired samples; more than two samples across a single factor; correlation; and linear regression. The volume also includes a section on advanced procedures and a final chapter on possible extensions into programming, featuring a discussion of algorithms, the art of looping, and combining programming and output.
Category: Science

Bioinformatics For Geneticists

Author : Michael R. Barnes
ISBN : 9780470026199
Genre : Computers
File Size : 48.97 MB
Format : PDF
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Bioinformatics for geneticists describes the key bioinformatics and genetic analysis processes that are needed to identify human genetic determinants. Including SNP functional analysis and statistical genetics.
Category: Computers

Molecular Pathology

Author : William B. Coleman
ISBN : 0123859123
Genre : Science
File Size : 21.18 MB
Format : PDF, ePub, Mobi
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Molecular Pathology: The Molecular Basis of Human Disease provides a current and comprehensive view of the molecular basis and mechanisms of human disease. Combining accepted principles with broader theoretical concepts and with contributions from a group of experts, the book looks into disease processes in the context of traditional pathology and their implications for translational molecular medicine. It also discusses concepts in molecular biology and genetics, recent scientific and technological advances in modern pathology, the concept of ""molecular pathogenesis"" of disease, and how disease evolves from normal cells and tissues due to perturbations in molecular pathways. The book describes the integration of molecular and cellular pathogenesis using a bioinformatics approach and a systems biology approach to disease pathogenesis. It also discusses current and future strategies in molecular diagnosis of human disease, and the impact of molecular diagnosis on treatment decisions and the practice of personalized medicine. This book is a valuable resource for students, biomedical researchers, practicing physician-scientists who undertake disease-related basic science and translational research, and pathology residents and other postdoctoral fellows. * Exam Master® web site will host "Self-assessment" questions that students can use to study for the molecular section of the board exam * Companion Web Site – will host a complete set of PowerPoint slides: to include images from the book and additional images for teaching; course materials; lecture materials * Teaches from the perspective of “integrative systems biology, which encompasses the intersection of all molecular aspects of biology, as applied to understanding human disease * Outlines the principles and practice of molecular pathology * Explains the practice of “molecular medicine and the translational aspects of molecular pathology
Category: Science

Dissecting The Molecular Anatomy Of Tissue

Author : Michael R. Emmert-Buck
ISBN : 3540220062
Genre : Medical
File Size : 56.59 MB
Format : PDF
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The book provides an updated overview of molecular analysis of human tissues, and the impact this analysis has on diagnosis and prognosis of human diseases. Special emphasis is placed on human cancer and the future directions of the field. Methods of handling clinical tissue samples, including the impact of handling on subsequent molecular analysis, are also discussed. In addition, detailed protocols for molecular analysis of DNA, RNA and protein, with special emphasis on molecular analysis of highly complex human tissue samples containing mixtures of cell populations, are provided.
Category: Medical

Microarray Technology In Practice

Author : Steve Russell
ISBN : 0080919766
Genre : Science
File Size : 83.98 MB
Format : PDF, ePub, Docs
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Using chips composed of thousands of spots, each with the capability of holding DNA molecules corresponding to a given gene, DNA microarray technology has enabled researchers to measure simultaneously gene expression across the genome. As with other large-scale genomics approaches, microarray technologies are broadly applicable across disciplines of life and biomedical sciences, but remain daunting to many researchers. This guide is designed to demystify the technology and inform more biologists about this critically important experimental technique. Cohesive overview of the technology and available platforms, followed by detailed discussion of experimental design and analysis of microarray experiments Up-to-date description of normalization methods and current methods for sample amplification and labeling Deep focus on oligonucleotide design, printing, labeling and hybridization, data acquisition, normalization, and meta-analysis Additional uses of microarray technology such as ChIP (chromatin immunoprecipitation) with hybridization to DNA arrays, microarray-based comparative genomic hybridization (CGH), and cell and tissue arrays
Category: Science