METHODS OF MICROARRAY DATA ANALYSIS III

Transcription

1 METHODS OF MICROARRAY DATA ANALYSIS III

2 METHODS OF MICROARRAY DATA ANALYSIS III Papers from CAMDA 02 edited by Kimberly F. Johnson Cancer Center Information Systems Duke University Medical Center Durham, NC Simon M. Lin Duke Bioinformatics Shared Resource Duke University Medical Center Durham, NC KLUWER ACADEMIC PUBLISHERS NEW YORK, BOSTON, DORDRECHT, LONDON, MOSCOW

3 ebook ISBN: Print ISBN: Springer Science + Business Media, Inc. Print 2003 Kluwer Academic Publishers Boston All rights reserved No part of this ebook may be reproduced or transmitted in any form or by any means, electronic, mechanical, recording, or otherwise, without written consent from the Publisher Created in the United States of America Visit Springer's ebookstore at: and the Springer Global Website Online at:

4 Contents Contributing Authors Preface Introduction SECTION I TUTORIALS THE BIOLOGY BEHIND GENE EXPRESSION: A BASIC TUTORIAL MICHAEL F. OCHS AND ERICA A. GOLEMIS MONITORING THE QUALITY OF MICROARRAY EXPERIMENTS KEVIN R. COOMBES, JING WANG, LYNNE V. ABRUZZO OUTLIERS IN MICROARRAY DATA ANALYSIS RONALD K. PEARSON, GREGORY E. GONYE, AND JAMES S. SCHWABER SECTION II BEST PRESENTATION AWARD ix xi ORGAN-SPECIFIC DIFFERENCES IN GENE EXPRESSION AND UNIGENE ANNOTATIONS DESCRIBING SOURCE MATERIAL 59 DAVID N. STIVERS, JING WANG, GARY L. ROSNER, AND KEVIN R. COOMBES SECTION III ANALYZING IMAGES 73

5 vi Methods of Microarray Data Analysis III CHARACTERIZATION, MODELING, AND SIMULATION OF MOUSE MICROARRAY DATA DAVID S. LALUSH TOPOLOGICAL ADJUSTMENTS TO GENECHIP EXPRESSION VALUES ANDREY PTITSYN SECTION IV NORMALIZING RAW DATA COMPARISON OF NORMALIZATION METHODS FOR CDNA MICROARRAYS LILING WARREN, BEN LIU SECTION V CHARACTERIZING TECHNICAL AND BIOLOGICAL VARIANCE 123 SIMULTANEOUS ASSESSMENT OF TRANSCRIPTOMIC VARIABILITY AND TISSUE EFFECTS IN THE NORMAL MOUSE 125 SHIBING DENG, TZU-MING CHU, AND RUSS WOLFINGER HOW MANY MICE AND HOW MANY ARRAYS? REPLICATION IN MOUSE CDNA MICROARRAY EXPERIMENTS XIANGQIN CUI AND GARY A. CHURCHILL 139 BAYESIAN CHARACTERIZATION OF NATURAL VARIATION IN GENE EXPRESSION 155 MADHUCHHANDA BHATTACHARJEE, COLIN PRITCHARD, MIKKO J. SlLLANPÄÄ AND ELJA ARJAS SECTION VI INVESTIGATING CROSS HYBRIDIZATION ON OLIGONUCLEOTIDE MICROARRAYS 173 QUANTIFICATION OF CROSS HYBRIDIZATION ON OLIGONUCLEOTIDE MICROARRAYS LI ZHANG, KEVIN R. COOMBES, LIANCHUN XIAO 175 ASSESSING THE POTENTIAL EFFECT OF CROSS-HYBRIDIZATION ON OLIGONUCLEOTIDE MICROARRAYS 185 SEMAN KACHALO, ZAREMA ARBIEVA AND JIE LIANG WHO ARE THOSE STRANGERS IN THE LATIN SQUARE? WEN-PING HSIEH, TZU-MING CHU, AND RUSS WOLFINGER 199

6 Methods of Microarray Data Analysis III vii SECTION VII FINDING PATTERNS AND SEEKING BIOLOGICAL EXPLANATIONS 209 BAYESIAN DECOMPOSITION CLASSIFICATION OF THE PROJECT NORMAL DATA SET 211 T. D. MOLOSHOK, D. DATTA, A. V. KOSSENKOV, M. F. OCHS THE USE OF GO TERMS TO UNDERSTAND THE BIOLOGICAL SIGNIFICANCE OF MICROARRAY DIFFERENTIALGENE EXPRESSION DATA 233 RAMÓN DÍAZ-URIARTE, FÁTIMA AL-SHAHROUR, AND JOAQUÍN DOPAZO Acknowledgments Index

7 Contributing Authors Abruzzo, Lynne V., University of Texas M.D. Anderson Cancer Center, Al-Shahrour, Fátima, Centro Nacional de Investigaciones Oncológicas, (CNIO), (Spanish National Cancer Centre), Madrid, Spain Arbieva, Zarema, University of Illinois at Chicago, Chicago, IL Arjas, Elja, Rolf Nevanlinna Institute, University of Helsinki, Finland Bhattacharjee, Madhuchhanda, Rolf Nevanlinna Institute, University of Helsinki, Finland Chu, Tzu-Ming, SAS Institute, Cary, NC Churchill, Gary A., The Jackson Laboratory, Bar Harbor, Maine Coombes, Kevin R., University of Texas M.D. Anderson Cancer Center, Cui, Xiangqin, The Jackson Laboratory, Bar Harbor, Maine Datta, D., Fox Chase Cancer Center, Philadelphia, PA Deng, Shibing, SAS Institute, Cary, NC Díaz-Uriarte, Ramón, Centro Nacional de Investigaciones Oncológicas, (CNIO), (Spanish National Cancer Centre), Madrid, Spain Dopazo, Joaquín, Centro Nacional de Investigaciones Oncológicas, (CNIO), (Spanish National Cancer Centre), Madrid, Spain Golemis, Erica A., Fox Chase Cancer Center, Philadelphia, PA Gonye, Gregory E., Thomas Jefferson University, Philadelphia, PA Hsieh, Wen-Ping, North Carolina State University, Raleigh, NC Kachalo, Seman, University of Illinois at Chicago, Chicago, IL Kossenkov, A. V., Fox Chase Cancer Center, Philadelphia, PA and Moscow Physical Engineering Institute, Moscow, Russian Federation Liang, Jie, University of Illinois at Chicago, Chicago, IL Liu, Ben, Bio-informatics Group Inc., Cary, NC Moloshok, T. D., Fox Chase Cancer Center, Philadelphia, PA Ochs, Michael F., Fox Chase Cancer Center, Philadelphia, PA Pearson, Ronald K., Thomas Jefferson University, Philadelphia, PA

8 x Contributing Authors Pritchard, Colin, Fred Hutchinson Cancer Research Centre, Seattle, WA Ptitsyn, Andrey, Pennington Biomedical Research Center Rosner, Gary L., University of Texas M.D. Anderson Cancer Center, Schwaber, James S, Thomas Jefferson University, Philadelphia, PA Sillanpää, Mikko J., Rolf Nevanlinna Institute, University of Helsinki, Finland Stivers, David N., University of Texas M.D. Anderson Cancer Center, Wang, Jing, University of Texas M.D. Anderson Cancer Center, Houston, TX Warren, Liling, Bio-informatics Group Inc., Cary, NC Wolfinger, Russ, SAS Institute, Cary, NC Xiao, Lianchun, The University of Texas MD Anderson Cancer Center, Zhang, Li, The University of Texas MD Anderson Cancer Center, Houston, TX

9 Preface As microarray technology has matured, data analysis methods have advanced as well. However, microarray results can vary widely from lab to lab as well as from chip to chip, with many opportunities for errors along the path from sample to data. The third CAMDA conference held in November of 2002 pointed out the increasing need for data quality assurance mechanisms through real world problems with the CAMDA datasets. Thus, the third volume of Methods of Microarray Data Analysis emphasizes many aspects of data quality assurance. We highlight three tutorial papers to assist with a basic understanding of underlying principles in microarray data analysis, and add twelve papers presented at the conference. As editors, we have not comprehensively edited these papers, but have provided comments to the authors to encourage clarity and expansion of ideas. Each paper was peer-reviewed and returned to the author for further revision. We do not propose these methods as the de facto standard for microarray analysis. But rather we present them as starting points for discussion to further the science of micrarray data analysis. The CAMDA conference continues to bring to light problems, solutions and new ideas to this arena and offers a forum for continued advancement of the art and science of microarray data analysis. Kimberly Johnson Simon Lin