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| dna methylation data analysis: Computational Genomics with R Altuna Akalin, 2020-12-16 Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015. |
| dna methylation data analysis: Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R Hongmei Zhang, 2020-05-14 Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline of analytical methods with concrete examples starting from raw gene expression and DNA methylation data at the genome scale. Methods on quality control, data pre-processing, data mining, and further assessments are presented in the book, and R programs based on simulated data and real data are included. Codes with example data are all reproducible. Features: • Provides a sequence of analytical tools for genome-scale gene expression data and DNA methylation data, starting from quality control and pre-processing of raw genome-scale data. • Organized by a parallel presentation with explanation on statistical methods and corresponding R packages/functions in quality control, pre-processing, and data analyses (e.g., clustering and networks). • Includes source codes with simulated and real data to reproduce the results. Readers are expected to gain the ability to independently analyze genome-scaled expression and methylation data and detect potential biomarkers. This book is ideal for students majoring in statistics, biostatistics, and bioinformatics and researchers with an interest in high dimensional genetic and epigenetic studies. |
| dna methylation data analysis: Next Generation Sequencing Jerzy Kulski, 2016-01-14 Next generation sequencing (NGS) has surpassed the traditional Sanger sequencing method to become the main choice for large-scale, genome-wide sequencing studies with ultra-high-throughput production and a huge reduction in costs. The NGS technologies have had enormous impact on the studies of structural and functional genomics in all the life sciences. In this book, Next Generation Sequencing Advances, Applications and Challenges, the sixteen chapters written by experts cover various aspects of NGS including genomics, transcriptomics and methylomics, the sequencing platforms, and the bioinformatics challenges in processing and analysing huge amounts of sequencing data. Following an overview of the evolution of NGS in the brave new world of omics, the book examines the advances and challenges of NGS applications in basic and applied research on microorganisms, agricultural plants and humans. This book is of value to all who are interested in DNA sequencing and bioinformatics across all fields of the life sciences. |
| dna methylation data analysis: Genome Data Analysis Ju Han Kim, 2019-04-30 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. |
| dna methylation data analysis: DNA Methylation Protocols Jörg Tost, 2018-08-30 This third edition volume expands on the previous editions by providing a comprehensive update on the available technologies required to successfully perform DNA methylation analysis. The different technologies discussed in this book analyze the global DNA methylation contents, comprehensive analyses using various NGS based methods for genome-wide DNA methylation analysis, along with precise quantification of DNA methylation levels on single CpG positions. The chapters in this book are divided into 7 parts: an introduction to the field along with tips on study design and data analysis; global DNA methylation levels; genome-wide DNA methylation analysis; highly multiplexed target regions; locus-specific DNA methylation analysis; DNA methylation analysis of specific biological samples; and hydroxymethylation. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, DNA Methylation Protocols, Third Edition is a valuable resource for postdoctoral investigators and research scientists who work with different aspects of genetics, and cellular and molecular biology, as well as clinicians who are involved in diagnostics or treatment of diseases with epigenetic components. |
| dna methylation data analysis: Computational Epigenetics and Diseases , 2019-02-06 Computational Epigenetics and Diseases, written by leading scientists in this evolving field, provides a comprehensive and cutting-edge knowledge of computational epigenetics in human diseases. In particular, the major computational tools, databases, and strategies for computational epigenetics analysis, for example, DNA methylation, histone modifications, microRNA, noncoding RNA, and ceRNA, are summarized, in the context of human diseases. This book discusses bioinformatics methods for epigenetic analysis specifically applied to human conditions such as aging, atherosclerosis, diabetes mellitus, schizophrenia, bipolar disorder, Alzheimer disease, Parkinson disease, liver and autoimmune disorders, and reproductive and respiratory diseases. Additionally, different organ cancers, such as breast, lung, and colon, are discussed. This book is a valuable source for graduate students and researchers in genetics and bioinformatics, and several biomedical field members interested in applying computational epigenetics in their research. - Provides a comprehensive and cutting-edge knowledge of computational epigenetics in human diseases - Summarizes the major computational tools, databases, and strategies for computational epigenetics analysis, such as DNA methylation, histone modifications, microRNA, noncoding RNA, and ceRNA - Covers the major milestones and future directions of computational epigenetics in various kinds of human diseases such as aging, atherosclerosis, diabetes, heart disease, neurological disorders, cancers, blood disorders, liver diseases, reproductive diseases, respiratory diseases, autoimmune diseases, human imprinting disorders, and infectious diseases |
| dna methylation data analysis: DNA Methylation and Complex Human Disease Michel Neidhart, 2015-08-11 DNA Methylation and Complex Human Disease reviews the possibilities of methyl-group-based epigenetic biomarkers of major diseases, tailored epigenetic therapies, and the future uses of high-throughput methylome technologies. This volume includes many pertinent advances in disease-bearing research, including obesity, type II diabetes, schizophrenia, and autoimmunity. DNA methylation is also discussed as a plasma and serum test for non-invasive screening, diagnostic and prognostic tests, as compared to biopsy-driven gene expression analysis, factors which have led to the use of DNA methylation as a potential tool for determining cancer risk, and diagnosis between benign and malignant disease. Therapies are at the heart of this volume and the possibilities of DNA demethylation. In cancer, unlike genetic mutations, DNA methylation and histone modifications are reversible and thus have shown great potential in the race for effective treatments. In addition, the authors present the importance of high-throughput methylome analysis, not only in cancer, but also in non-neoplastic diseases such as rheumatoid arthritis. - Discusses breaking biomarker research in major disease families of current health concern and research interest, including obesity, type II diabetes, schizophrenia, and autoimmunity - Summarizes advances not only relevant to cancer, but also in non-neoplastic disease, currently an emerging field - Describes wholly new concepts, including the linking of metabolic pathways with epigenetics - Provides translational researchers with the knowledge of both basic research and clinic applications of DNA methylation in human diseases |
| dna methylation data analysis: Toxicoepigenetics Shaun D. McCullough, Dana Dolinoy, 2018-11-02 Toxicoepigenetics: Core Principles and Applications examines the core aspects of epigenetics, including chromatin biology, DNA methylation, and non-coding RNA, as well as fundamental techniques and considerations for studying each of these mechanisms of epigenetic regulation. Although its integration into the field of toxicology is in its infancy, epigenetics have taken center stage in the study of diseases such as cancer, diabetes, and neurodegeneration. Increasing the presence of epigenetics in toxicological research allows for a more in-depth understanding of important aspects of toxicology such as the role of the environment and lifestyle influencing the individual susceptibility to these effects and the trans-generational transmission of these health effects and susceptibilities. Methods chapters are included to help improve efficacy and efficiency of protocols in both the laboratory and the classroom. Toxicoepigenetics: Core Principles and Applications is an essential book for researchers and academics using epigenetics in toxicology research and study. - Introduces the fundamental principles and practices for understanding the role of the epigenome in toxicology - Presents the foundation of epigenetics for toxicologists with a broad range of backgrounds - Discusses the incorporation of epigenetics and epigenomics into current toxicological studies and interpretation of epigenetic data in toxicological applications |
| dna methylation data analysis: DNA Methylation Jörg Tost, 2010-12-01 Over the past few years, DNA methylation technologies and our knowledge of DNA methylation patterns have been advancing at a breathtaking pace. Due to this fact, DNA Methylation: Methods and Protocols, Second Edition completely revises, updates, and expands upon the popular first edition with the most current novel techniques, easier to use and more refined by the tested experience of leading experts. This revision reflects contemporary study of the subject: the analysis of gene-specific DNA methylation patterns has been complemented by genome-wide approaches, and epigenomics takes a central place. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters in this volume present brief introductions to the topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and notes which highlight tips on troubleshooting and avoiding known pitfalls. Comprehensive and cutting-edge, DNA Methylation: Methods and Protocols, Second Edition is the perfect resource for scientists who wish to further our understanding of the molecular processes that determine the genomic DNA methylation landscape and for those who aim to identify and implement DNA methylation-based biomarkers for clinical and diagnostic applications. |
| dna methylation data analysis: Cancer Bioinformatics Alexander Krasnitz, 2018-11-18 This volume covers a wide variety of state of the art cancer-related methods and tools for data analysis and interpretation. Chapters were designed to attract a broad readership, ranging from active researchers in computational biology and bioinformatics developers, clinical oncologists, and anti-cancer drug developers wishing to rationalize their search for new compounds. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, installation instructions for computational tools discussed, explanations of the input and output formats, and illustrative examples of applications. Authoritative and cutting-edge, Cancer Bioinformatics: Methods and Protocols aims to support researchers performing computational analysis of cancer-related data. |
| dna methylation data analysis: DNA Modifications Alexey Ruzov, Martin Gering, 2020-08-22 This book provides an overview of methods and experimental protocols that are currently used to analyze the presence and abundance of non-canonical DNA nucleotides in different biological systems. Focusing particularly on the newly discovered and less studied DNA modifications that are enzymatically produced and are likely to play specific roles in various biological processes, the volume explores chromatography- and mass spectrometry-based techniques for the detection and quantification of DNA modifications, antibody-based approaches to study their spatial distribution in different cells and tissues, and methods to analyze their genomic distribution with the help of bioinformatics tools that interrogate the corresponding datasets. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and comprehensive, DNA Modifications: Methods and Protocols serves as an ideal guide to research scientists and PhD students in this rapidly developing discipline, and, thus, will ultimately contribute to deciphering the roles of non-canonical DNA nucleotides in different biological systems. |
| dna methylation data analysis: Oral Biology Gregory J. Seymour, Mary P. Cullinan, Nicholas C.K. Heng, Paul R. Cooper, 2022-11-23 This fully revised new edition explores advances in the prevention and treatment of oral diseases. Beyond the updated chapters, the book delves into regenerative biology, gene editing and the use of CRISPR in oral biology, as well as histone acetylation and deacetylation methods, further reflecting advances in the application of molecular techniques to oral biology. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step and readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and up-to-date, Oral Biology: Molecular Techniques and Applications, Third Edition serves as an ideal basic resource not only for new researchers but also for experienced scientists wishing to expand their research platform into new areas of this vital field. |
| dna methylation data analysis: Epigenome Editing Albert Jeltsch, |
| dna methylation data analysis: Epigenetics Protocols Trygve O. Tollefsbol, 2004-07-23 The field of epigenetics has grown exponentially in the past decade, and a steady flow of exciting discoveries in this area has served to move it to the forefront of molecular biology. Although epigenetics may previously have been considered a peripheral science, recent advances have shown considerable progress in unraveling the many mysteries of nontraditional genetic processes. Given the fast pace of epigenetic discoveries and the groundbreaking nature of these developments, a thorough treatment of the methods in the area seems timely and appropriate and is the goal of Epigenetics Protocols. The scope of epigenetics is vast, and an exhaustive analysis of all of the techniques employed by investigators would be unrealistic. However, this TM volume of Methods in Molecular Biology covers three main areas that should be of greatest interest to epigenetics investigators: (1) techniques related to analysis of chromatin remodeling, such as histone acetylation and methylation; (2) methods in newly developed and especially promising areas of epigenetics such as telomere position effects, quantitative epigenetics, and ADP ribosylation; and (3) an updated analysis of techniques involving DNA methylation and its role in the modification, as well as the maintenance, of chromatin structure. |
| dna methylation data analysis: Next-Generation Sequencing Data Analysis Xinkun Wang, 2016-04-06 A Practical Guide to the Highly Dynamic Area of Massively Parallel SequencingThe development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphi |
| dna methylation data analysis: Epigenetics and Metabolomics Paban K. Agrawala, Poonam Rana, 2021-08-25 Epigenetics and Metabolomics, a new volume in the Translational Epigenetics series, offers a synthesized discussion of epigenetic control of metabolic activity, and systems-based approaches for better understanding these mechanisms. Over a dozen chapter authors provide an overview of epigenetics in translational medicine and metabolomics techniques, followed by analyses of epigenetic and metabolomic linkage mechanisms likely to result in effective identification of disease biomarkers, as well as new therapies targeting the removal of the inappropriate epigenetic alterations. Epigenetic interventions in cancer, brain damage, and neuroendocrine disease, among other disorders, are discussed in-depth, with an emphasis on exploring next steps for clinical translation and personalized healthcare. - Offers a synthesized discussion of epigenetic regulation of metabolic activity and systems-based approaches to power new research - Discusses epigenetic control of metabolic pathways and possible therapeutic targets for cancer, neurodegenerative, and neuroendocrine diseases, among others - Provides guidance in epigenomics and metabolomic research methodology |
| dna methylation data analysis: Epigenetic Epidemiology Karin B. Michels, 2012-01-02 The exploding field of epigenetics is challenging the dogma of traditional Mendelian inheritance. Epigenetics plays an important role in shaping who we are and contributes to our prospects of health and disease. While early epigenetic research focused on plant and animal models and in vitro experiments, population-based epidemiologic studies increasingly incorporate epigenetic components. The relevance of epigenetic marks, such as DNA methylation, genomic imprinting, and histone modification for disease causation has yet to be fully explored.This book covers the basic concepts of epigenetic epidemiology, discusses challenges in study design, analysis, and interpretation, epigenetic laboratory techniques, the influence of age and environmental factors on shaping the epigenome, the role of epigenetics in the developmental origins hypothesis, and provides the state of the art on the epigenetic epidemiology of various health conditions including childhood syndromes, cancer, infectious diseases, inflammation and rheumatoid arthritis, asthma, autism and other neurodevelopmental disorders, psychiatric disorders, diabetes, obesity and metabolic disorders, and atherosclerosis. With contributions from: Peter Jones, Jean-Pierre Issa, Gavin Kelsey, Robert Waterland, and many other experts in epigenetics! |
| dna methylation data analysis: Pyrosequencing Protocols Sharon Marsh, 2008-02-04 This book presents detailed protocols for the multidisciplinary application of Pyrosequencing® technology, all written by world-renowned experts. This comprehensive volume enables quick reference by collecting the primary applications for Pyrosequencing®, and supplementing each protocol with troubleshooting tips specific to that method. This volume both highlights the versatility of and provides detailed protocols for the application of Pyrosequencing®. |
| dna methylation data analysis: Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R Hongmei Zhang, 2020-05-14 Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline of analytical methods with concrete examples starting from raw gene expression and DNA methylation data at the genome scale. Methods on quality control, data pre-processing, data mining, and further assessments are presented in the book, and R programs based on simulated data and real data are included. Codes with example data are all reproducible. Features: • Provides a sequence of analytical tools for genome-scale gene expression data and DNA methylation data, starting from quality control and pre-processing of raw genome-scale data. • Organized by a parallel presentation with explanation on statistical methods and corresponding R packages/functions in quality control, pre-processing, and data analyses (e.g., clustering and networks). • Includes source codes with simulated and real data to reproduce the results. Readers are expected to gain the ability to independently analyze genome-scaled expression and methylation data and detect potential biomarkers. This book is ideal for students majoring in statistics, biostatistics, and bioinformatics and researchers with an interest in high dimensional genetic and epigenetic studies. |
| dna methylation data analysis: Epigenetics of Aging Trygve O. Tollefsbol, 2009-11-11 Recent studies have indicated that epigenetic processes may play a major role in both cellular and organismal aging. These epigenetic processes include not only DNA methylation and histone modifications, but also extend to many other epigenetic mediators such as the polycomb group proteins, chromosomal position effects, and noncoding RNA. The topics of this book range from fundamental changes in DNA methylation in aging to the most recent research on intervention into epigenetic modifications to modulate the aging process. The major topics of epigenetics and aging covered in this book are: 1) DNA methylation and histone modifications in aging; 2) Other epigenetic processes and aging; 3) Impact of epigenetics on aging; 4) Epigenetics of age-related diseases; 5) Epigenetic interventions and aging: and 6) Future directions in epigenetic aging research. The most studied of epigenetic processes, DNA methylation, has been associated with cellular aging and aging of organisms for many years. It is now apparent that both global and gene-specific alterations occur not only in DNA methylation during aging, but also in several histone alterations. Many epigenetic alterations can have an impact on aging processes such as stem cell aging, control of telomerase, modifications of telomeres, and epigenetic drift can impact the aging process as evident in the recent studies of aging monozygotic twins. Numerous age-related diseases are affected by epigenetic mechanisms. For example, recent studies have shown that DNA methylation is altered in Alzheimer’s disease and autoimmunity. Other prevalent diseases that have been associated with age-related epigenetic changes include cancer and diabetes. Paternal age and epigenetic changes appear to have an effect on schizophrenia and epigenetic silencing has been associated with several of the progeroid syndromes of premature aging. Moreover, the impact of dietary or drug intervention into epigenetic processes as they affect normal aging or age-related diseases is becoming increasingly feasible. |
| dna methylation data analysis: Bioinformatics and Biomedical Engineering Ignacio Rojas, Olga Valenzuela, Fernando Rojas, Luis Javier Herrera, Francisco Ortuño, 2020-04-30 This volume constitutes the proceedings of the 8th International Work-Conference on IWBBIO 2020, held in Granada, Spain, in May 2020. The total of 73papers presented in the proceedings, was carefully reviewed and selected from 241 submissions. The papers are organized in topical sections as follows: Biomarker Identification; Biomedical Engineering; Biomedical Signal Analysis; Bio-Nanotechnology; Computational Approaches for Drug Design and Personalized Medicine; Computational Proteomics and Protein-Protein Interactions; Data Mining from UV/VIS/NIR Imaging and Spectrophotometry; E-Health Technology, Services and Applications; Evolving Towards Digital Twins in Healthcare (EDITH); High Performance in Bioinformatics; High-Throughput Genomics: Bioinformatic Tools and Medical Applications; Machine Learning in Bioinformatics; Medical Image Processing; Simulation and Visualization of Biological Systems. |
| dna methylation data analysis: Data Analysis for the Life Sciences with R Rafael A. Irizarry, Michael I. Love, 2016-10-04 This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained. |
| dna methylation data analysis: Environmental Epigenetics L. Joseph Su, Tung-chin Chiang, 2015-05-18 This book examines the toxicological and health implications of environmental epigenetics and provides knowledge through an interdisciplinary approach. Included in this volume are chapters outlining various environmental risk factors such as phthalates and dietary components, life states such as pregnancy and ageing, hormonal and metabolic considerations and specific disease risks such as cancer cardiovascular diseases and other non-communicable diseases. Environmental Epigenetics imparts integrative knowledge of the science of epigenetics and the issues raised in environmental epidemiology. This book is intended to serve both as a reference compendium on environmental epigenetics for scientists in academia, industry and laboratories and as a textbook for graduate level environmental health courses. Environmental Epigenetics imparts integrative knowledge of the science of epigenetics and the issues raised in environmental epidemiology. This book is intended to serve both as a reference compendium on environmental epigenetics for scientists in academia, industry and laboratories and as a textbook for graduate level environmental health courses. |
| dna methylation data analysis: Biomedical Statistics Shakti Kumar Yadav, Sompal Singh, Ruchika Gupta, 2019-11-23 This book is written in a very easy-to-follow format, and explains the key concepts of biomedical statistics in a lucid yet straightforward manner. It explains how mathematical and statistical tools can be used to find answers to common research questions. In addition, the main text is supplemented by a wealth of solved exercises and illustrative examples to aid in comprehension. Given its content, the book offers an invaluable quick reference guide for graduating students and can be very helpful in their examination process. At the same time, it represents a handy guide for medical and paramedical teachers, post-graduate medical students, research personnel, biomedical scientists and epidemiologists. |
| dna methylation data analysis: Digital PCR George Karlin-Neumann, Francisco Bizouarn, 2018-05-01 This volume explores and explains how digital PCRs (dPCRs) help in the study of numerous topics, such as infectious diseases, evolution of cancer and treatment responses, somatic mosaicism, genome editing and cell therapy, and food testing for GMOs and pathogens. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and thorough, Digital PCR: Methods and Protocols is a valuable resource for specialists in various fields, including geneticists, neurologists, immunologists, oncologists, and researchers who are interested in environmental sciences.” |
| dna methylation data analysis: Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing Ana M. Aransay, José Luis Lavín Trueba, 2016-06-02 High throughput sequencing (HTS) technologies have conquered the genomics and epigenomics worlds. The applications of HTS methods are wide, and can be used to sequence everything from whole or partial genomes, transcriptomes, non-coding RNAs, ribosome profiling, to single-cell sequencing. Having such diversity of alternatives, there is a demand for information by research scientists without experience in HTS that need to choose the most suitable methodology or combination of platforms and to define their experimental designs to achieve their specific objectives. Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing aims to collect in a single volume all aspects that should be taken into account when HTS technologies are being incorporated into a research project and the reasons behind them. Moreover, examples of several successful strategies will be analyzed to make the point of the crucial features. This book will be of use to all scientist that are unfamiliar with HTS and want to incorporate such technologies to their research. |
| dna methylation data analysis: Neurobehavioral Genetics Byron C. Jones, Pierre Mormede, 2006-08-30 A complete background to concepts and principles of behavioral genetics, Neurobehavioral Genetics: Methods and Applications, Second Edition features a broad spectrum of the most current techniques in neurobehavioral genetics in a single source. International researchers incorporate several new developments in the field, including: De |
| dna methylation data analysis: Computational and Statistical Epigenomics Andrew E. Teschendorff, 2015-05-12 This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK. |
| dna methylation data analysis: Chromatin Julia Horsfield, Judith Marsman, 2022 This volume provides cutting-edge techniques to further the study chromatin biology. Chapters include both novel and well-established methods for the analysis of DNA-associated proteins, DNA methylation, three-dimensional chromatin interactions, deep sequencing-based tools, and data analysis pipelines. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, provides details of the necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and describes step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Chromatin: Methods and Protocols aims to further the understanding of how modified DNA and associated proteins affect the transcriptional output of the genome. Chapter Genome-wide mapping and microscopy visualization of protein-DNA interactions by pA-DamID [Chapter 12] is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| dna methylation data analysis: Weighted Network Analysis Steve Horvath, 2011-04-30 High-throughput measurements of gene expression and genetic marker data facilitate systems biologic and systems genetic data analysis strategies. Gene co-expression networks have been used to study a variety of biological systems, bridging the gap from individual genes to biologically or clinically important emergent phenotypes. |
| dna methylation data analysis: Genomics in the Cloud Geraldine A. Van der Auwera, Brian D. O'Connor, 2020-04-02 Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytesâ??or over 50 million gigabytesâ??of genomic data, and theyâ??re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian Oâ??Connor of the UC Santa Cruz Genomics Institute, guide you through the process. Youâ??ll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra |
| dna methylation data analysis: Epigenetics Methods Trygve O Tollefsbol, 2020-07-08 In recent years, the field of epigenetics has grown significantly, driving new understanding of human developmental processes and disease expression, as well as advances in diagnostics and therapeutics. As the field of epigenetics continues to grow, methods and technologies have multiplied, resulting in a wide range of approaches and tools researchers might employ. Epigenetics Methods offers comprehensive instruction in methods, protocols, and experimental approaches applied in field of epigenetics. Here, across thirty-five chapters, specialists offer step-by-step overviews of methods used to study various epigenetic mechanisms, as employed in basic and translational research. Leading the reader from fundamental to more advanced methods, the book begins with thorough instruction in DNA methylation techniques and gene or locus-specific methylation analyses, followed by histone modification methods, chromatin evaluation, enzyme analyses of histone methylation, and studies of non-coding RNAs as epigenetic modulators. Recently developed techniques and technologies discussed include single-cell epigenomics, epigenetic editing, computational epigenetics, systems biology epigenetic methods, and forensic epigenetic approaches. Epigenetics methods currently in-development, and their implication for future research, are also considered in-depth. In addition, as with the wider life sciences, reproducibility across experiments, labs, and subdisciplines is a growing issue for epigenetics researchers. This volume provides consensus-driven methods instruction and overviews. Tollefsbol and contributing authors survey the range of existing methods; identify best practices, common themes, and challenges; and bring unity of approach to a diverse and ever-evolving field. - Includes contributions by leading international investigators involved in epigenetic research and clinical and therapeutic application - Integrates technology and translation with fundamental chapters on epigenetics methods, as well as chapters on more novel and advanced epigenetics methods - Written at verbal and technical levels that can be understood by scientists and students alike - Includes chapters on state-of-the-art techniques such as single-cell epigenomics, use of CRISPR/Cas9 for epigenetic editing, and epigenetics methods applied to forensics |
| dna methylation data analysis: Flow Cytometry with Plant Cells Jaroslav Dolezel, Johann Greilhuber, Jan Suda, 2007-06-27 Targeted at beginners as well as experienced users, this handy reference explains the benefits and uses of flow cytometery in the study of plants and their genomes. Following a brief introduction that highlights general considerations when analyzing plant cells by flow cytometric methods, the book goes on to discuss examples of application in plant genetics, genomic analysis, cell cycle analysis, marine organism analysis and breeding studies. With its list of general reading and a glossary of terms, this first reference on FCM in plants fills a real gap by providing first-hand practical hints for the growing community of plant geneticists. |
| dna methylation data analysis: International Conference on Innovative Computing and Communications Ashish Khanna, Deepak Gupta, Siddhartha Bhattacharyya, Aboul Ella Hassanien, Sameer Anand, Ajay Jaiswal, 2021-09-01 This book includes high-quality research papers presented at the Fourth International Conference on Innovative Computing and Communication (ICICC 2021), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 20–21, 2021. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications. |
| dna methylation data analysis: Plant Transposable Elements Jungnam Cho, 2022-05-11 This volume details the most up-to-date technologies used in plant transposable element studies and provides easy-to-follow protocols. Chapters guide readers on available database resources, annotation of different families of transposon, and experimental methods to detect their transposition intermediates, neo-transposed DNAs, and transposition events. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Plant Transposable Elements: Methods and Protocols aims to provide web-lab and dry-lab methodologies targeted at various levels from beginner to experienced. |
| dna methylation data analysis: TET Proteins and DNA Demethylation Ozren Bogdanovic, Michiel Vermeulen, 2021-05-20 This volume explores the latest methods used to study various aspects of TET proteins and their biology. Chapters in this book are divided into five parts. Part One describes technologies aimed at detecting and quantifying DNA methylation turnover using massively parallel sequencing, ELISA, and mass spectrometry approaches. Part Two looks at data analyses protocols for distinguishing acting versus passive DNA demethylation and estimation of 5mC and 5hmC levels. Part Three deals with a new topic that takes advantage of modified CRISPR/Cas9 genome editing systems to target DNA demethylation activity to genomic loci of interest. Part Four discusses protocols that detail how to purify TET proteins and unravel their protein interactions, and Part Five looks at the assessment of TET protein function and activity in vivo and in vitro. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, TET Proteins and DNA Demethylation: Methods and Protocols is a valuable resource that aims to help research scientists at all levels working in the fields of DNA demethylation dynamics. Chapters 3, 7 and 17 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| dna methylation data analysis: Epigenomics Krishnarao Appasani, 2012-08-02 Understanding mechanisms of gene regulation that are independent of the DNA sequence itself - epigenetics - has the potential to overthrow long-held views on central topics in biology, such as the biology of disease or the evolution of species. High throughput technologies reveal epigenetic mechanisms at a genome-wide level, giving rise to epigenomics as a new discipline with a distinct set of research questions and methods. Leading experts from academia, the biotechnology and pharmaceutical industries explain the role of epigenomics in a wide range of contexts, covering basic chromatin biology, imprinting at a genome-wide level, and epigenomics in disease biology and epidemiology. Details on assays and sequencing technology serve as an up-to-date overview of the available technological tool kit. A reliable guide for newcomers to the field as well as experienced scientists, this is a unique resource for anyone interested in applying the power of twenty-first-century genomics to epigenetic studies. |
| dna methylation data analysis: CpG Islands Tanya Vavouri, Miguel A. Peinado, 2018-04-01 This detailed volume examines bioinformatic and molecular biological methods useful to identify and to explore the functions of CpG islands, key navigation points to understand gene regulation in fundamental processes such as development and cell differentiation as well as in diseases like cancer. Beginning with a historical perspective and important properties of CpG islands, the book continues with sections on computational and wet lab methods related to the study of DNA methylation, and in-depth protocols for the analysis of CpG island functional features including epigenetic profiling and chromatin interactions. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, CpG Islands: Methods and Protocols aims to provide readers with the information and methodologies necessary to continue to decipher how a genome’s structure and organization contribute to regulate biological processes. |
| dna methylation data analysis: Continuous Bivariate Distributions N. Balakrishnan, Chin Diew Lai, 2009-05-31 Along with a review of general developments relating to bivariate distributions, this volume also covers copulas, a subject which has grown immensely in recent years. In addition, it examines conditionally specified distributions and skewed distributions. |
| dna methylation data analysis: Big Data in Omics and Imaging Momiao Xiong, 2018-06-14 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. |
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