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Computer Science/Bioinformatics Second Edition Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides U f S o a clear and rigorous description of powerful analysis techniques t s r a and algorithms for mining and interpreting biological information. i t n M Omitting tedious details, heavy formalisms, and cryptic notations, i g s the text takes a hands-on, example-based approach that explains i t the basics of R and microarray technology as well as how to choose R c i c and apply the proper data analysis tool to specific problems. r o s a New to the Second Edition n a a Completely updated and double the size of its predecessor, this r n d r timely second edition replaces the commercial software with the open d a source R and Bioconductor environments. Fourteen new chapters B y D cover such topics as the basic mechanisms of the cell, reliability i s o and reproducibility issues in DNA microarrays, basic statistics and a c linear models in R, experiment design, multiple comparisons, quality t o a control, data pre-processing and normalization, gene ontology n A analysis, pathway analysis, and machine learning techniques. d Methods are illustrated with toy examples and real data, and the R n u code for all routines is available on an accompanying CD-ROM. a c l With all the necessary prerequisites included, this best-selling t y o book guides readers from very basic notions to advanced analysis s r techniques in R and Bioconductor. The first half of the text presents i s an overview of microarrays and the statistical elements that form the building blocks of any data analysis. The second half introduces the techniques most commonly used in the analysis of microarray data. D r a˘ g h i c i K10487 K10487_Cover.indd 1 9/14/11 1:33 PM Statistics and Data Analysis for Microarrays Using R and Bioconductor Second Edition K10487_FM.indd 1 9/14/11 2:21 PM CHAPMAN & HALL/CRC Mathematical and Computational Biology Series Aims and scope: This series aims to capture new developments and summarize what is known over the entire spectrum of mathematical and computational biology and medicine. It seeks to encourage the integration of mathematical, statistical, and computational methods into biology by publishing a broad range of textbooks, reference works, and handbooks. The titles included in the series are meant to appeal to students, researchers, and professionals in the mathematical, statistical and computational sciences, fundamental biology and bioengineering, as well as interdisciplinary researchers involved in the field. The inclusion of concrete examples and applications, and programming techniques and examples, is highly encouraged. Series Editors N. F. Britton Department of Mathematical Sciences University of Bath Xihong Lin Department of Biostatistics Harvard University Hershel M. Safer School of Computer Science Tel Aviv University Maria Victoria Schneider European Bioinformatics Institute Mona Singh Department of Computer Science Princeton University Anna Tramontano Department of Biochemical Sciences University of Rome La Sapienza Proposals for the series should be submitted to one of the series editors above or directly to: CRC Press, Taylor & Francis Group 4th, Floor, Albert House 1-4 Singer Street London EC2A 4BQ UK K10487_FM.indd 2 9/14/11 2:21 PM Published Titles Algorithms in Bioinformatics: A Practical Exactly Solvable Models of Biological Introduction Invasion Wing-Kin Sung Sergei V. Petrovskii and Bai-Lian Li Bioinformatics: A Practical Approach Gene Expression Studies Using Shui Qing Ye Affymetrix Microarrays Hinrich Göhlmann and Willem Talloen Biological Computation Ehud Lamm and Ron Unger Glycome Informatics: Methods and Applications Biological Sequence Analysis Using Kiyoko F. Aoki-Kinoshita the SeqAn C++ Library Andreas Gogol-Döring and Knut Reinert Handbook of Hidden Markov Models in Bioinformatics Cancer Modelling and Simulation Martin Gollery Luigi Preziosi Introduction to Bioinformatics Cancer Systems Biology Anna Tramontano Edwin Wang Introduction to Bio-Ontologies Cell Mechanics: From Single Scale- Peter N. Robinson and Sebastian Bauer Based Models to Multiscale Modeling Arnaud Chauvière, Luigi Preziosi, Introduction to Computational and Claude Verdier Proteomics Golan Yona Clustering in Bioinformatics and Drug Discovery Introduction to Proteins: Structure, John D. MacCuish and Norah E. MacCuish Function, and Motion Amit Kessel and Nir Ben-Tal Combinatorial Pattern Matching Algorithms in Computational Biology An Introduction to Systems Biology: Using Perl and R Design Principles of Biological Circuits Gabriel Valiente Uri Alon Computational Biology: A Statistical Kinetic Modelling in Systems Biology Mechanics Perspective Oleg Demin and Igor Goryanin Ralf Blossey Knowledge Discovery in Proteomics Computational Hydrodynamics of Igor Jurisica and Dennis Wigle Capsules and Biological Cells Meta-analysis and Combining C. Pozrikidis Information in Genetics and Genomics Computational Neuroscience: Rudy Guerra and Darlene R. Goldstein A Comprehensive Approach Methods in Medical Informatics: Jianfeng Feng Fundamentals of Healthcare Data Analysis Tools for DNA Microarrays Programming in Perl, Python, and Ruby Sorin Draghici Jules J. Berman Differential Equations and Mathematical Modeling and Simulation of Capsules Biology, Second Edition and Biological Cells D.S. Jones, M.J. Plank, and B.D. Sleeman C. Pozrikidis Dynamics of Biological Systems Niche Modeling: Predictions from Michael Small Statistical Distributions David Stockwell Engineering Genetic Circuits Chris J. Myers K10487_FM.indd 3 9/14/11 2:21 PM Published Titles (continued) Normal Mode Analysis: Theory and Statistics and Data Analysis for Applications to Biological and Chemical Microarrays Using R and Bioconductor, Systems Second Edition Qiang Cui and Ivet Bahar Sorin Dra˘ghici Optimal Control Applied to Biological Stochastic Modelling for Systems Models Biology Suzanne Lenhart and John T. Workman Darren J. Wilkinson Pattern Discovery in Bioinformatics: Structural Bioinformatics: An Algorithmic Theory & Algorithms Approach Laxmi Parida Forbes J. Burkowski Python for Bioinformatics The Ten Most Wanted Solutions in Sebastian Bassi Protein Bioinformatics Anna Tramontano Spatial Ecology Stephen Cantrell, Chris Cosner, and Shigui Ruan Spatiotemporal Patterns in Ecology and Epidemiology: Theory, Models, and Simulation Horst Malchow, Sergei V. Petrovskii, and Ezio Venturino K10487_FM.indd 4 9/14/11 2:21 PM Statistics and Data Analysis for Microarrays Using R and Bioconductor Second Edition Sorin Dra˘ghici K10487_FM.indd 5 9/14/11 2:21 PM CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2012 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Version Date: 2011909 International Standard Book Number-13: 978-1-4398-0976-1 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources. 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For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com To Jeannette, my better half, to Tavi, who brightens every day of my life, and to Althea, whom I miss every day we are not together This page intentionally left blank Contents List of Figures xxv List of Tables xxxv Preface xxxix 1 Introduction 1 1.1 Bioinformatics – an emerging discipline . . . . . . . . . . . . 1 2 The cell and its basic mechanisms 5 2.1 The cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 The building blocks of genomic information . . . . . . . . . . 13 2.2.1 The deoxyribonucleic acid (DNA) . . . . . . . . . . . 13 2.2.2 The DNA as a language . . . . . . . . . . . . . . . . . 19 2.2.3 Errors in the DNA language. . . . . . . . . . . . . . . 23 2.2.4 Other useful concepts . . . . . . . . . . . . . . . . . . 24 2.3 Expression of genetic information . . . . . . . . . . . . . . . 28 2.3.1 Transcription . . . . . . . . . . . . . . . . . . . . . . . 30 2.3.2 Translation . . . . . . . . . . . . . . . . . . . . . . . . 32 2.3.3 Gene regulation. . . . . . . . . . . . . . . . . . . . . . 35 2.4 The need for high-throughput methods . . . . . . . . . . . . 36 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3 Microarrays 39 3.1 Microarrays– tools for gene expression analysis . . . . . . . 39 3.2 Fabrication of microarrays . . . . . . . . . . . . . . . . . . . 41 3.2.1 Deposition . . . . . . . . . . . . . . . . . . . . . . . . 41 3.2.1.1 The Illumina technology . . . . . . . . . . . 42 3.2.2 In situ synthesis . . . . . . . . . . . . . . . . . . . . . 48 3.2.3 A brief comparison of cDNA and oligonucleotide tech- nologies . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.3 Applications of microarrays . . . . . . . . . . . . . . . . . . . 57 3.4 Challenges in using microarraysin gene expression studies . 58 ix