An Introduction to High Content Screening

Imaging Technology, Assay Development, and Data Analysis in Biology and Drug Discovery
Herausgegeben von Haney, Steven A.; Bowman, Douglas; Chakravarty, Arijit; Davies, Anthony; Shamu, Caroline

• Gebundenes Buch

Produktbeschreibung

Using a collaborative and interdisciplinary author base with experience in the pharmaceutical industry and academia, this book is a practical resource for high content (HC) techniques.

- Instructs readers on the fundamentals of high content screening (HCS) techniques
- Focuses on practical and widely-used techniques like image processing and multiparametric assays
- Breaks down HCS into individual modules for training and connects them at the end
- Includes a tutorial chapter that works through sample HCS assays, glossary, and detailed appendices

Produktdetails

• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 352
• Erscheinungstermin: 7. Januar 2015
• Englisch
• Abmessung: 240mm x 161mm x 23mm
• Gewicht: 666g
• ISBN-13: 9780470624562
• ISBN-10: 0470624566
• Artikelnr.: 41640952

Autorenporträt

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.

Inhaltsangabe

PREFACE xvii CONTRIBUTORS xix 1 Introduction 1 Steven A. Haney 1.1 The Beginning of High Content Screening
1 1.2 Six Skill Sets Essential for Running HCS Experiments
4 1.3 Integrating Skill Sets into a Team
7 1.4 A Few Words on Experimental Design
8 1.5 Conclusions
9 Key Points
9 Further Reading
10 References
10 SECTION I FIRST PRINCIPLES 11 2 Fluorescence and Cell Labeling 13 Anthony Davies and Steven A. Haney 2.1 Introduction
13 2.2 Anatomy of Fluorescent Probes
Labels
and Dyes
14 2.3 Stokes' Shift and Biological Fluorophores
15 2.4 Fluorophore Properties
16 2.5 Localization of Fluorophores Within Cells
18 2.6 Multiplexing Fluorescent Reagents
26 2.7 Specialized Imaging Applications Derived from Complex Properties of Fluorescence
27 2.8 Conclusions
30 Key Points
31 Further Reading
31 References
31 3 Microscopy Fundamentals 33 Steven A. Haney
Anthony Davies
and Douglas Bowman 3.1 Introducing HCS Hardware
33 3.2 Deconstructing Light Microscopy
37 3.3 Using the Imager to Collect Data
43 3.4 Conclusions
45 Key Points
45 Further Reading
46 References
46 4 Image Processing 47 John Bradley
Douglas Bowman
and Arijit Chakravarty 4.1 Overview of Image Processing and Image Analysis in HCS
47 4.2 What is a Digital Image?
48 4.3 "Addressing" Pixel Values in Image Analysis Algorithms
48 4.4 Image Analysis Workflow
49 4.5 Conclusions
60 Key Points
60 Further Reading
60 References
60 SECTION II GETTING STARTED 63 5 A General Guide to Selecting and Setting Up a High Content Imaging Platform 65 Craig Furman
Douglas Bowman
Anthony Davies
Caroline Shamu
and Steven A. Haney 5.1 Determining Expectations of the HCS System
65 5.2 Establishing an HC Platform Acquisition Team
66 5.3 Basic Hardware Decisions
67 5.4 Data Generation
Analysis
and Retention
72 5.5 Installation
73 5.6 Managing the System
75 5.7 Setting Up Workflows for Researchers
77 5.8 Conclusions
78 Key Points
79 Further Reading
79 6 Informatics Considerations 81 Jay Copeland and Caroline Shamu 6.1 Informatics Infrastructure for High Content Screening
81 6.2 Using Databases to Store HCS Data
86 6.3 Mechanics of an Informatics Solution
89 6.4 Developing Image Analysis Pipelines: Data Management Considerations
95 6.5 Compliance With Emerging Data Standards
99 6.6 Conclusions
101 Key Points
102 Further Reading
102 References
102 7 Basic High Content Assay Development 103 Steven A. Haney and Douglas Bowman 7.1 Introduction
103 7.2 Initial Technical Considerations for Developing a High Content Assay
103 7.3 A Simple Protocol to Fix and Stain Cells
107 7.4 Image Capture and Examining Images
109 7.5 Conclusions
111 Key Points
112 Further Reading
112 Reference
112 SECTION III ANALYZING DATA 113 8 Designing Metrics for High Content Assays 115 Arijit Chakravarty
Steven A. Haney
and Douglas Bowman 8.1 Introduction: Features
Metrics
Results
115 8.2 Looking at Features
116 8.3 Metrics and Results: The Metric is the Message
120 8.4 Types of High Content Assays and Their Metrics
121 8.5 Metrics to Results: Putting it all Together
126 8.6 Conclusions
128 Key Points
128 Further Reading
129 References
129 9 Analyzing Well-Level Data 131 Steven A. Haney 9.1 Introduction
131 9.2 Reviewing Data
132 9.3 Plate and Control Normalizations of Data
134 9.4 Calculation of Assay Statistics
135 9.5 Data Analysis: Hit Selection
138 9.6 IC 50 Determinations
139 9.7 Conclusions
143 Key Points
143 Further Reading
143 References
144 10 Analyzing Cell-Level Data 145 Steven A. Haney
Lin Guey
and Arijit Chakravarty 10.1 Introduction
145 10.2 Understanding General Statistical Terms and Concepts
146 10.3 Examining Data
149 10.4 Developing a Data Analysis Plan
155 10.5 Cell-Level Data Analysis: Comparing Distributions Through Inferential Statistics
158 10.6 Analyzing Normal (or Transformed) Data
159 10.7 Analyzing Non-Normal Data
160 10.8 When to Call For Help
162 10.9 Conclusions
162 Key Points
162 Further Reading
163 References
163 SECTION IV ADVANCED WORK 165 11 Designing Robust Assays 167 Arijit Chakravarty
Douglas Bowman
Anthony Davies
Steven A. Haney
and Caroline Shamu 11.1 Introduction
167 11.2 Common Technical Issues in High Content Assays
167 11.3 Designing Assays to Minimize Trouble
172 11.4 Looking for Trouble: Building in Quality Control
177 11.5 Conclusions
179 Key Points
180 Further Reading
180 References
180 12 Automation and Screening 181 John Donovan
Arijit Chakravarty
Anthony Davies
Steven A. Haney
Douglas Bowman
John Ringeling
and Ben Knight 12.1 Introduction
181 12.2 Some Preliminary Considerations
181 12.3 Laboratory Options
183 12.4 The Automated HCS Laboratory
186 12.5 Conclusions
192 Key Points
192 Further Reading
193 13 High Content Analysis for Tissue Samples 195 Kristine Burke
Vaishali Shinde
Alice McDonald
Douglas Bowman
and Arijit Chakravarty 13.1 Introduction
195 13.2 Design Choices in Setting Up a High Content Assay in Tissue
196 13.3 System Configuration: Aspects Unique to Tissue-Based HCS
199 13.4 Data Analysis
203 13.5 Conclusions
207 Key Points
207 Further Reading
207 References
208 SECTION V HIGH CONTENT ANALYTICS 209 14 Factoring and Clustering High Content Data 211 Steven A. Haney 14.1 Introduction
211 14.2 Common Unsupervised Learning Methods
212 14.3 Preparing for an Unsupervised Learning Study
218 14.4 Conclusions
228 Key Points
228 Further Reading
228 References
229 15 Supervised Machine Learning 231 Jeff Palmer and Arijit Chakravarty 15.1 Introduction
231 15.2 Foundational Concepts
232 15.3 Choosing a Machine Learning Algorithm
234 15.4 When Do You Need Machine Learning
and How Do You Use IT?
243 15.5 Conclusions
244 Key Points
244 Further Reading
244 Appendix A Websites and Additional Information on Instruments
Reagents
and Instruction 247 Appendix B A Few Words About One Letter: Using R to Quickly Analyze HCS Data 249 Steven A. Haney B.1 Introduction
249 B.2 Setting Up R
250 B.3 Analyzing Data in R
253 B.4 Where to Go Next
261 Further Reading
263 Appendix C Hypothesis Testing for High Content Data: A Refresher 265 Lin Guey and Arijit Chakravarty C.1 Introduction
265 C.2 Defining Simple Hypothesis Testing
266 C.3 Simple Statistical Tests to Compare Two Groups
269 C.4 Statistical Tests on Groups of Samples
276 C.5 Introduction to Regression Models
280 C.6 Conclusions
285 Key Concepts
286 Further Reading
286 GLOSSARY 287 TUTORIAL 295 INDEX 323