Download or read book Application of the Empirical Bayes Method in a Comparative Microarray Experiment written by Ying Wang and published by . This book was released on 2002 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Empirical Bayes Analysis of a Microarray Experiment written by and published by . This book was released on 2001 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Comparison of the Empirical Bayes and the Significance Analysis of Microarrays written by Holger Schwender and published by . This book was released on 2003 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Analysis of Gene Expression Data written by Giovanni Parmigiani and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.
Download or read book Sample Size Calculation and Empirical Bayes Tests for Microarray Data written by Peng Liu and published by . This book was released on 2006 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bayesian and Empirical Bayes Approaches to Power Law Process and Microarray Analysis written by Zhao Chen and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: The prediction results for the software reliability model are illustrated. We compare our result with the result of Bar-Lev, S.K. et al. Also, posterior densities of several parametric functions are given. Chapter 4 provides Empirical Bayes for the power law process with natural conjugate priors and nonparametric priors. For the natural conjugate priors, two-hyperparameter prior and a more generalized three-hyperparameter prior are used. In chapter 5, we review some basic statistical procedures that are involved in microarray analysis. We will also present and compare several transformation and normalization methods for probe level data. The objective of chapter 6 is to select differentially expressed genes from tens of thousands of genes. Both classical methods (fold change, T-test, Wilcoxon Rank-sum Test, SAM and local Z-score and Empirical Bayes methods (EBarrays and LIMMA) are applied to obtain the results.
Download or read book Resampling Based Multiple Testing written by Peter H. Westfall and published by John Wiley & Sons. This book was released on 1993-01-12 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power.
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.
Download or read book Empirical Bayes Methods for DNA Microarray Data written by Ingrid Lönnstedt and published by . This book was released on 2005 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Analysis of Gene Expression Microarray Data written by Terry Speed and published by CRC Press. This book was released on 2003-03-26 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies
Download or read book Statistical Problems in DNA Microarray Data Analysis written by Nancy Naichao Wang and published by . This book was released on 2009 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: DNA microarrays are powerful tools for functional genomics studies. Each array contains thousands of microscopic spots of DNA oligonucleotides with specific sequences, which can hybridize with their complementary DNA sequences. Thus each microarray experiment consists of parallel assays about thousands of genomic fragments. This thesis concerns some statistical issues in the analysis of DNA microarray data. One common usage of DNA microarrays is to monitor the dynamic levels of gene expression in response to a stimulus. This is often achieved through a time course experiment, in which RNA samples are extracted at various time points after exposing the organism to the stimulus. A particularly interesting type of time course experiments involve replicated series of longitudinal samples. In 2006, Tai and Speed proposed a multivariate empirical Bayes model for analyzing this type of data. The MB-statistic derived from this model was shown useful for ranking the genes according to changes in their temporal expression profiles. In the first part of this thesis, we propose an empirical Bayes false discovery rate (FDR)-controlling procedure for multiple hypothesis testing using the MB-statistic. A null distribution is obtained using the parametric bootstrap. Critical values are determined according to the empirical Bayes FDR procedure. This method was compared, through simulations, to the frequentist FDR procedure, which requires a theoretical null distribution for calculating the nominal p-values. Although our method is slightly anti-conservative, it is more robust to the variability in the estimates of the hyperparameters, when the degree of moderation is small. Another common usage of DNA microarrays is to detect genomic locations that are associated with DNA-binding proteins. This is often achieved through ChIP-chip experiments that combine chromatin immunoprecipitation with the microarray technology. Traditional DNA microarrays designed for gene expression studies contain only a few probes for each gene. A special type of DNA microarrays, called tiling arrays, are often used in ChIP-chip experiments. They typically contain probes that are placed densely along the chromosomes to cover either the entire genome or contigs of the genome. A couple of challenges in the analysis of ChIP-chip tiling array data have not been met satisfactorily in the literature. When large scale genomic studies are carried over a long period of time, tiling arrays with different probe designs are often used for practical reasons. The first challenge is the integration of replicate experiments performed using different tiling array designs. When the biological process of interest involves a large protein complex, the investigators often perform ChIP-chip experiments on each component DNA-binding protein individually. DNA targets that are shared by the individual proteins are thought to be the localization sites of the protein complex. The second challenge is the joint analysis of multiple DNA-binding proteins, aimed at identifying their shared targets. In the second part of this thesis, we propose a nonhomogeneous hidden Markov model (HMM) for addressing these two challenges. The nonhomogeneous time axis represents the genomic positions of the probes. The hidden states represent the binding statuses of the proteins. The state-conditional emission distributions of the tiling array data are protein-specific and design-specific. We derived a modified Baum-Welch algorithm for fitting the model parameters. We also developed a procedure that converts the probe level summaries into peaks, which represent the putative binding sites, based on both signal strength and peak shape. To compare our method with existing methods, we curated a set of positive and negative genomic regions from a C. elegans dataset, and performed some receiver operating characteristics (ROC) analyses. When applied to each experiment separately, our method performs similarly as the three best existing methods. When applied to the combined data set, which consists of tiling arrays with different probe designs, our method shows a drastic improvement in performance. A generalization of the nonhomogeneous HMM enables the joint analysis of the ChIP-chip data of multiple proteins. We present an application of this method to identify the shared localization sites of two DNA-binding proteins, under two different conditions.
Download or read book Handbook of Statistical Genomics written by David J. Balding and published by John Wiley & Sons. This book was released on 2019-07-09 with total page 1828 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.
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.
Download or read book Large Scale Inference written by Bradley Efron and published by Cambridge University Press. This book was released on 2012-11-29 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.
Download or read book 16th International Conference on Information Technology New Generations ITNG 2019 written by Shahram Latifi and published by Springer. This book was released on 2019-05-22 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 16th International Conference on Information Technology - New Generations (ITNG), continues an annual event focusing on state of the art technologies pertaining to digital information and communications. The applications of advanced information technology to such domains as astronomy, biology, education, geosciences, security and health care are among topics of relevance to ITNG. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help the information readily flow to the user are of special interest. Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing are examples of related topics. The conference features keynote speakers, the best student award, poster award, service award, a technical open panel, and workshops/exhibits from industry, government and academia.
Download or read book DNA Microarrays and Related Genomics Techniques written by David B. Allison and published by CRC Press. This book was released on 2005-11-14 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches
Download or read book Understanding Bioinformatics written by Marketa J. Zvelebil and published by Garland Science. This book was released on 2008 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for advanced undergraduates & postgraduates, this book provides a definitive guide to bioinformatics. It takes a conceptual approach & guides the reader from first principles through to an understanding of the computational techniques & the key algorithms.
