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Statistical And Computational Methods For Comparing High Throughput Data From Two Conditions
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Book Synopsis Statistical and Computational Methods for Comparing High-Throughput Data from Two Conditions by : Xinzhou Ge
Download or read book Statistical and Computational Methods for Comparing High-Throughput Data from Two Conditions written by Xinzhou Ge and published by . This book was released on 2021 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of high-throughput biological technologies have enabled researchers to simultaneously perform analysis on thousands of features (e.g., genes, genomic regions, and proteins). The most common goal of analyzing high-throughput data is to contrast two conditions, to identify ``interesting'' features, whose values differ between two conditions. How to contrast the features from two conditions to extract useful information from high-throughput data, and how to ensure the reliability of identified features are two increasingly pressing challenge to statistical and computational science. This dissertation aim to address these two problems regarding analysing high-throughput data from two conditions. My first project focuses on false discovery rate (FDR) control in high-throughput data analysis from two conditions. FDR is defined as the expected proportion of uninteresting features among the identified ones. It is the most widely-used criterion to ensure the reliability of the interesting features identified. Existing bioinformatics tools primarily control the FDR based on p-values. However, obtaining valid p-values relies on either reasonable assumptions of data distribution or large numbers of replicates under both conditions, two requirements that are often unmet in biological studies. In Chapter \ref{chap:clipper}, we propose Clipper, a general statistical framework for FDR control without relying on p-values or specific data distributions. Clipper is applicable to identifying both enriched and differential features from high-throughput biological data of diverse types. In comprehensive simulation and real-data benchmarking, Clipper outperforms existing generic FDR control methods and specific bioinformatics tools designed for various tasks, including peak calling from ChIP-seq data, and differentially expressed gene identification from bulk or single-cell RNA-seq data. Our results demonstrate Clipper's flexibility and reliability for FDR control, as well as its broad applications in high-throughput data analysis. My second project focuses on alignment of multi-track epigenomic signals from different samples or conditions. The availability of genome-wide epigenomic datasets enables in-depth studies of epigenetic modifications and their relationships with chromatin structures and gene expression. Various alignment tools have been developed to align nucleotide or protein sequences in order to identify structurally similar regions. However, there are currently no alignment methods specifically designed for comparing multi-track epigenomic signals and detecting common patterns that may explain functional or evolutionary similarities. We propose a new local alignment algorithm, EpiAlign, designed to compare chromatin state sequences learned from multi-track epigenomic signals and to identify locally aligned chromatin regions. EpiAlign is a dynamic programming algorithm that novelly incorporates varying lengths and frequencies of chromatin states. We demonstrate the efficacy of EpiAlign through extensive simulations and studies on the real data from the NIH Roadmap Epigenomics project. EpiAlign can also detect common chromatin state patterns across multiple epigenomes from conditions, and it will serve as a useful tool to group and distinguish epigenomic samples based on genome-wide or local chromatin state patterns.
Book Synopsis Genetics Meets Metabolomics by : Karsten Suhre
Download or read book Genetics Meets Metabolomics written by Karsten Suhre and published by Springer Science & Business Media. This book was released on 2012-06-15 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is written by leading researchers in the fields about the intersection of genetics and metabolomics which can lead to more comprehensive studies of inborn variation of metabolism.
Book Synopsis Computational Methods for Single-Cell Data Analysis by : Guo-Cheng Yuan
Download or read book Computational Methods for Single-Cell Data Analysis written by Guo-Cheng Yuan and published by Humana Press. This book was released on 2019-02-14 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. 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, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.
Book Synopsis Optimal High-Throughput Screening by : Xiaohua Douglas Zhang
Download or read book Optimal High-Throughput Screening written by Xiaohua Douglas Zhang and published by Cambridge University Press. This book was released on 2011-02-21 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, self-contained and cohesive book focuses on commonly used and recently developed methods for designing and analyzing high-throughput screening (HTS) experiments from a statistically sound basis. Combining ideas from biology, computing and statistics, the author explains experimental designs and analytic methods that are amenable to rigorous analysis and interpretation of RNAi HTS experiments. The opening chapters are carefully presented to be accessible both to biologists with training only in basic statistics and to computational scientists and statisticians with basic biological knowledge. Biologists will see how new experiment designs and rudimentary data-handling strategies for RNAi HTS experiments can improve their results, whereas analysts will learn how to apply recently developed statistical methods to interpret HTS experiments.
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 Computational Methods for the Analysis of Genomic Data and Biological Processes by : Francisco A. Gómez Vela
Download or read book Computational Methods for the Analysis of Genomic Data and Biological Processes written by Francisco A. Gómez Vela and published by MDPI. This book was released on 2021-02-05 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.
Book Synopsis Computational Genomics with R by : Altuna Akalin
Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Evolution of Translational Omics by : Institute of Medicine
Download or read book Evolution of Translational Omics written by Institute of Medicine and published by National Academies Press. This book was released on 2012-09-13 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.
Book Synopsis Methods in Yeast Genetics by : David C. Amberg
Download or read book Methods in Yeast Genetics written by David C. Amberg and published by CSHL Press. This book was released on 2005 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Methods in Yeast Genetics" is a course that has been offered annually at Cold Spring Harbor for the last 30 years. This provides a set of teaching experiments along with the protocols and recipes for the standard techniques and reagents used in the study of yeast biology.
Book Synopsis High-Throughput Metabolomics by : Angelo D'Alessandro
Download or read book High-Throughput Metabolomics written by Angelo D'Alessandro and published by Humana. This book was released on 2020-06-06 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed volume focuses on recent technological, computational, and biostatistical advances in the field of high-throughput metabolomics. Chapters encompass methods, platforms, and analytical strategies for steady state measurements and metabolic flux analysis with stable isotope-labeled tracers, in biological matrices of clinical relevance and model organisms. Mass spectrometry-based or orthogonal methods are discussed, along with computational and statistical methods to address data sparsity in high-throughput metabolomics approaches. As a part of 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 practical, High-Throughput Metabolomics: Methods and Protocols provides tools that can bring about the next generation of clinical biochemistry in a cost-effective, rigorous fashion, exponentially advancing our capacity to investigate nature while hastening the advent of personalized medicine.
Book Synopsis Differential Expression Analysis for Sequence Count Data by : Applied Research Press
Download or read book Differential Expression Analysis for Sequence Count Data written by Applied Research Press and published by Createspace Independent Publishing Platform. This book was released on 2015-07-24 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package. Proceeds from the sale of this book go to the support of an elderly disabled person.
Book Synopsis Batch Effects and Noise in Microarray Experiments by : Andreas Scherer
Download or read book Batch Effects and Noise in Microarray Experiments written by Andreas Scherer and published by John Wiley & Sons. This book was released on 2009-11-03 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Batch Effects and Noise in Microarray Experiments: Sources and Solutions looks at the issue of technical noise and batch effects in microarray studies and illustrates how to alleviate such factors whilst interpreting the relevant biological information. Each chapter focuses on sources of noise and batch effects before starting an experiment, with examples of statistical methods for detecting, measuring, and managing batch effects within and across datasets provided online. Throughout the book the importance of standardization and the value of standard operating procedures in the development of genomics biomarkers is emphasized. Key Features: A thorough introduction to Batch Effects and Noise in Microrarray Experiments. A unique compilation of review and research articles on handling of batch effects and technical and biological noise in microarray data. An extensive overview of current standardization initiatives. All datasets and methods used in the chapters, as well as colour images, are available on www.the-batch-effect-book.org, so that the data can be reproduced. An exciting compilation of state-of-the-art review chapters and latest research results, which will benefit all those involved in the planning, execution, and analysis of gene expression studies.
Book Synopsis Metagenomics by : Muniyandi Nagarajan
Download or read book Metagenomics written by Muniyandi Nagarajan and published by Academic Press. This book was released on 2017-10-29 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metagenomics: Perspectives, Methods, and Applications provides thorough coverage of the growing field of metagenomics. A diverse range of chapters from international experts offer an introduction to the field and examine methods for metagenomic analysis of microbiota, metagenomic computational tools, and recent metagenomic studies in various environments. The emphasis on application makes this text particularly useful for applied researchers, practitioners, clinicians and students seeking to employ metagenomic approaches to advance knowledge in the biomedical and life sciences. Case-study based application chapters examine topics ranging from viral metagenome profiling, metagenomics in oral disease and health, metagenomic insights into the human gut microbiome and metabolic syndromes, and more. Additionally, perspectives on future potential at the end of each chapter provoke new thought and motivations for continued study in this exciting and fruitful research area. Provides thorough coverage of the rapidly growing field of metagenomics, with an emphasis on applications of relevance to translational researchers, practitioners, clinicians and students Features a diverse range of chapters from international experts that offer an introduction to the field and examine methods for metagenomic analysis of microbiota, metagenomic computational tools and research pipelines Highlights perspectives on future potential at the end of each chapter to provoke new thought and motivations for continued study in this exciting and fruitful research area
Book Synopsis Introduction to Computational Genomics by : Nello Cristianini
Download or read book Introduction to Computational Genomics written by Nello Cristianini and published by Cambridge University Press. This book was released on 2006-12-14 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book.
Book Synopsis The Statistical Analysis of Compositional Data by : John Aitchison
Download or read book The Statistical Analysis of Compositional Data written by John Aitchison and published by . This book was released on 2003 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1986, this text contains a new Foreword, extensive postscript detailing developments in the field since its first publication, and a selection of more recent literature references. The work provides a clear and systematic account of statistical methods designed to meet the special needs of the compositional data analyst. (Mathematics)
Book Synopsis Directed Enzyme Evolution by : Frances H. Arnold
Download or read book Directed Enzyme Evolution written by Frances H. Arnold and published by Springer Science & Business Media. This book was released on 2008-02-02 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Directed evolution comprises two distinct steps that are typically applied in an iterative fashion: (1) generating molecular diversity and (2) finding among the ensemble of mutant sequences those proteins that perform the desired fu- tion according to the specified criteria. In many ways, the second step is the most challenging. No matter how cleverly designed or diverse the starting library, without an effective screening strategy the ability to isolate useful clones is severely diminished. The best screens are (1) high throughput, to increase the likelihood that useful clones will be found; (2) sufficiently sen- tive (i. e. , good signal to noise) to allow the isolation of lower activity clones early in evolution; (3) sufficiently reproducible to allow one to find small improvements; (4) robust, which means that the signal afforded by active clones is not dependent on difficult-to-control environmental variables; and, most importantly, (5) sensitive to the desired function. Regarding this last point, almost anyone who has attempted a directed evolution experiment has learned firsthand the truth of the dictum “you get what you screen for. ” The protocols in Directed Enzyme Evolution describe a series of detailed p- cedures of proven utility for directed evolution purposes. The volume begins with several selection strategies for enzyme evolution and continues with assay methods that can be used to screen enzyme libraries. Genetic selections offer the advantage that functional proteins can be isolated from very large libraries s- ply by growing a population of cells under selective conditions.
Download or read book MiRNomics written by Malik Yousef and published by . This book was released on 2014 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: In miRNomics: MicroRNA Biology and Computational Analysis, expert researchers in the field present an overview of the current state of the art and aim to put the respective areas of research into a larger perspective. These include methods and techniques ranging from miRNA biogenesis, their biological function, computational analyses to their medical implications and applications. 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 key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, miRNomics: MicroRNA Biology and Computational Analysis seeks to aid scientists in the further study into miRNA research and statistics.
