The Analysis of Gene Expression Data

Methods and Software

  • Giovanni Parmigiani
  • Elizabeth S. Garrett
  • Rafael A. Irizarry
  • Scott L. Zeger

Part of the Statistics for Biology and Health book series (SBH)

Table of contents

  1. Front Matter
    Pages i-xix
  2. Giovanni Parmigiani, Elizabeth S. Garrett, Rafael A. Irizarry, Scott L. Zeger
    Pages 1-45
  3. Robert Gentleman, Vincent Carey
    Pages 46-72
  4. Rafael A. Irizarry, Laurent Gautier, Leslie M. Cope
    Pages 102-119
  5. Cheng Li, Wing Hung Wong
    Pages 120-141
  6. Jaak Vilo, Misha Kapushesky, Patrick Kemmeren, Ugis Sarkans, Alvis Brazma
    Pages 142-162
  7. Christopher M. L. S. Bouton, George Henry, Carlo Colantuoni, Jonathan Pevsner
    Pages 185-209
  8. Carlo Colantuoni, George Henry, Christopher M. L. S. Bouton, Scott L. Zeger, Jonathan Pevsner
    Pages 210-228
  9. Peter F. Lemkin, Gregory C. Thornwall, Jai Evans
    Pages 229-253
  10. Michael A. Newton, Christina Kendziorski
    Pages 254-271
  11. Yi Lin, Samuel T. Nadler, Hong Lan, Alan D. Attie, Brian S. Yandell
    Pages 291-312
  12. Hao Wu, M. Kathleen Kerr, Xiangqin Cui, Gary A. Churchill
    Pages 313-341
  13. Kim-Anh Do, Bradley Broom, Sijin Wen
    Pages 342-361
  14. Elizabeth S. Garrett, Giovanni Parmigiani
    Pages 362-387
  15. Michael F. Ochs
    Pages 388-408
  16. Paola Sebastiani, Marco Ramoni, Isaac S. Kohane
    Pages 409-427

About this book

Introduction

Thedevelopmentoftechnologiesforhigh–throughputmeasurementofgene expression in biological system is providing powerful new tools for inv- tigating the transcriptome on a genomic scale, and across diverse biol- ical systems and experimental designs. This technological transformation is generating an increasing demand for data analysis in biological inv- tigations of gene expression. This book focuses on data analysis of gene expression microarrays. The goal is to provide guidance to practitioners in deciding which statistical approaches and packages may be indicated for their projects, in choosing among the various options provided by those packages, and in correctly interpreting the results. The book is a collection of chapters written by authors of statistical so- ware for microarray data analysis. Each chapter describes the conceptual and methodological underpinning of data analysis tools as well as their software implementation, and will enable readers to both understand and implement an analysis approach. Methods touch on all aspects of statis- cal analysis of microarrays, from annotation and ?ltering to clustering and classi?cation. All software packages described are free to academic users. The materials presented cover a range of software tools designed for varied audiences. Some chapters describe simple menu-driven software in a user-friendly fashion and are designed to be accessible to microarray data analystswithoutformalquantitativetraining.Mostchaptersaredirectedat microarray data analysts with master’s-level training in computer science, biostatistics, or bioinformatics. A minority of more advanced chapters are intended for doctoral students and researchers.

Keywords

ANOVA Clustering Computer DNA DNA-Chip Master Patient Index Microarray Parametric statistics bioinformatics biostatistics cluster analysis data analysis genes modeling statistics

Editors and affiliations

  • Giovanni Parmigiani
    • 1
  • Elizabeth S. Garrett
    • 2
  • Rafael A. Irizarry
    • 3
  • Scott L. Zeger
    • 4
  1. 1.Departments of Oncology, Biostatistics,and PathologyJohns Hopkins UniversityBaltimoreUSA
  2. 2.Departments of Oncology and BiostatisticsJohns Hopkins UniversityBaltimoreUSA
  3. 3.Departments of BiostatisticsJohns Hopkins UniversityBaltimoreUSA
  4. 4.Departments of Biostatistics and EpidemiologyJohns Hopkins UniversityBaltimoreUSA

Bibliographic information

  • DOI https://doi.org/10.1007/b97411
  • Copyright Information Springer Science+Business Media New York 2003
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-95577-3
  • Online ISBN 978-0-387-21679-9
  • Series Print ISSN 1431-8776
  • Series Online ISSN 2197-5671
  • About this book