Introduction To High Content Screening

Steven Haney is a Senior Research Advisor and Group Leader at Eli Lilly and Company. He edited the book High Content Screening: Science, Techniques, and Applications (Wiley, 2008).Douglas Bowman is an Associate Scientific Fellow at Takeda Pharmaceuticals.Arijit Chakravarty is the Director of Modeling and Simulation (DMPK) at Takeda Pharmaceuticals.Anthony Davies is Center Director, Translational Cell Imaging, Queensland University Of Technology, Queensland, Australia.Caroline Shamu is the Director of the ICCB-Longwood Screening Facility at Harvard Medical School.

• PREFACE xviiCONTRIBUTORS xix1 Introduction 1Steven A. Haney1.1 The Beginning of High Content Screening, 11.2 Six Skill Sets Essential for Running HCS Experiments, 41.3 Integrating Skill Sets into a Team, 71.4 A Few Words on Experimental Design, 81.5 Conclusions, 9Key Points, 9Further Reading, 10References, 10SECTION I FIRST PRINCIPLES 112 Fluorescence and Cell Labeling 13Anthony Davies and Steven A. Haney2.1 Introduction, 132.2 Anatomy of Fluorescent Probes, Labels, and Dyes, 142.3 Stokes’ Shift and Biological Fluorophores, 152.4 Fluorophore Properties, 162.5 Localization of Fluorophores Within Cells, 182.6 Multiplexing Fluorescent Reagents, 262.7 Specialized Imaging Applications Derived from Complex Properties of Fluorescence, 272.8 Conclusions, 30Key Points, 31Further Reading, 31References, 313 Microscopy Fundamentals 33Steven A. Haney, Anthony Davies, and Douglas Bowman3.1 Introducing HCS Hardware, 333.2 Deconstructing Light Microscopy, 373.3 Using the Imager to Collect Data, 433.4 Conclusions, 45Key Points, 45Further Reading, 46References, 464 Image Processing 47John Bradley, Douglas Bowman, and Arijit Chakravarty4.1 Overview of Image Processing and Image Analysis in HCS, 474.2 What is a Digital Image?, 484.3 “Addressing” Pixel Values in Image Analysis Algorithms, 484.4 Image Analysis Workflow, 494.5 Conclusions, 60Key Points, 60Further Reading, 60References, 60SECTION II GETTING STARTED 635 A General Guide to Selecting and Setting Up a High Content Imaging Platform 65Craig Furman, Douglas Bowman, Anthony Davies, Caroline Shamu, and Steven A. Haney5.1 Determining Expectations of the HCS System, 655.2 Establishing an HC Platform Acquisition Team, 665.3 Basic Hardware Decisions, 675.4 Data Generation, Analysis, and Retention, 725.5 Installation, 735.6 Managing the System, 755.7 Setting Up Workflows for Researchers, 775.8 Conclusions, 78Key Points, 79Further Reading, 796 Informatics Considerations 81Jay Copeland and Caroline Shamu6.1 Informatics Infrastructure for High Content Screening, 816.2 Using Databases to Store HCS Data, 866.3 Mechanics of an Informatics Solution, 896.4 Developing Image Analysis Pipelines: Data Management Considerations, 956.5 Compliance With Emerging Data Standards, 996.6 Conclusions, 101Key Points, 102Further Reading, 102References, 1027 Basic High Content Assay Development 103Steven A. Haney and Douglas Bowman7.1 Introduction, 1037.2 Initial Technical Considerations for Developing a High Content Assay, 1037.3 A Simple Protocol to Fix and Stain Cells, 1077.4 Image Capture and Examining Images, 1097.5 Conclusions, 111Key Points, 112Further Reading, 112Reference, 112SECTION III ANALYZING DATA 1138 Designing Metrics for High Content Assays 115Arijit Chakravarty, Steven A. Haney, and Douglas Bowman8.1 Introduction: Features, Metrics, Results, 1158.2 Looking at Features, 1168.3 Metrics and Results: The Metric is the Message, 1208.4 Types of High Content Assays and Their Metrics, 1218.5 Metrics to Results: Putting it all Together, 1268.6 Conclusions, 128Key Points, 128Further Reading, 129References, 1299 Analyzing Well-Level Data 131Steven A Haney and John Ringeling9.1 Introduction, 1319.2 Reviewing Data, 1329.3 Plate and Control Normalizations of Data, 1349.4 Calculation of Assay Statistics, 1359.5 Data Analysis: Hit Selection, 1389.6 IC 50 Determinations, 1399.7 Conclusions, 143Key Points, 143Further Reading, 143References, 14410 Analyzing Cell-Level Data 145Steven A. Haney, Lin Guey, and Arijit Chakravarty10.1 Introduction, 14510.2 Understanding General Statistical Terms and Concepts, 14610.3 Examining Data, 14910.4 Developing a Data Analysis Plan, 15510.5 Cell-Level Data Analysis: Comparing Distributions Through Inferential Statistics, 15810.6 Analyzing Normal (or Transformed) Data, 15910.7 Analyzing Non-Normal Data, 16010.8 When to Call For Help, 16210.9 Conclusions, 162Key Points, 162Further Reading, 163References, 163SECTION IV ADVANCED WORK 16511 Designing Robust Assays 167Arijit Chakravarty, Douglas Bowman, Anthony Davies, Steven A. Haney, and Caroline Shamu11.1 Introduction, 16711.2 Common Technical Issues in High Content Assays, 16711.3 Designing Assays to Minimize Trouble, 17211.4 Looking for Trouble: Building in Quality Control, 17711.5 Conclusions, 179Key Points, 180Further Reading, 180References, 18012 Automation and Screening 181John Ringeling, John Donovan, Arijit Chakravarty, Anthony Davies, Steven A Haney, Douglas Bowman, and Ben Knight12.1 Introduction, 18112.2 Some Preliminary Considerations, 18112.3 Laboratory Options, 18312.4 The Automated HCS Laboratory, 18612.5 Conclusions, 192Key Points, 192Further Reading, 19313 High Content Analysis for Tissue Samples 195Kristine Burke, Vaishali Shinde, Alice McDonald, Douglas Bowman, and Arijit Chakravarty13.1 Introduction, 19513.2 Design Choices in Setting Up a High Content Assay in Tissue, 19613.3 System Configuration: Aspects Unique to Tissue-Based HCS, 19913.4 Data Analysis, 20313.5 Conclusions, 207Key Points, 207Further Reading, 207References, 208SECTION V HIGH CONTENT ANALYTICS 20914 Factoring and Clustering High Content Data 211Steven A. Haney14.1 Introduction, 21114.2 Common Unsupervised Learning Methods, 21214.3 Preparing for an Unsupervised Learning Study, 21814.4 Conclusions, 228Key Points, 228Further Reading, 228References, 22915 Supervised Machine Learning 231Jeff Palmer and Arijit Chakravarty15.1 Introduction, 23115.2 Foundational Concepts, 23215.3 Choosing a Machine Learning Algorithm, 23415.4 When Do You Need Machine Learning, and How Do You Use IT?, 24315.5 Conclusions, 244Key Points, 244Further Reading, 244Appendix A Websites and Additional Information on Instruments, Reagents, and Instruction 247Appendix B A Few Words About One Letter: Using R to Quickly Analyze HCS Data 249Steven A. HaneyB.1 Introduction, 249B.2 Setting Up R, 250B.3 Analyzing Data in R, 253B.4 Where to Go Next, 261Further Reading, 263Appendix C Hypothesis Testing for High Content Data: A Refresher 265Lin Guey and Arijit ChakravartyC.1 Introduction, 265C.2 Defining Simple Hypothesis Testing, 266C.3 Simple Statistical Tests to Compare Two Groups, 269C.4 Statistical Tests on Groups of Samples, 276C.5 Introduction to Regression Models, 280C.6 Conclusions, 285Key Concepts, 286Further Reading, 286GLOSSARY 287TUTORIAL 295INDEX 323