The effect of replication on gene expression microarray experiments

被引:104
作者
Pavlidis, P
Li, QH
Noble, WS
机构
[1] Columbia Univ, Columbia Genome Ctr, New York, NY 10032 USA
[2] Columbia Univ, Dept Comp Sci, New York, NY 10027 USA
[3] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA
关键词
D O I
10.1093/bioinformatics/btg227
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: We examine the effect of replication on the detection of apparently differentially expressed genes in gene expression microarray experiments. Our analysis is based on a random sampling approach using real data sets from 16 published studies. We consider both the ability to find genes that meet particular statistical criteria as well as the stability of the results in the face of changing levels of replication. Results: While dependent on the data source, our findings suggest that stable results are typically not obtained until at least five biological replicates have been used. Conversely, for most studies, 10-15 replicates yield results that are quite stable, and there is less improvement in stability as the number of replicates is further increased. Our methods will be of use in evaluating existing data sets and in helping to design new studies.
引用
收藏
页码:1620 / 1627
页数:8
相关论文
共 22 条
[1]  
Allander SV, 2001, CANCER RES, V61, P8624
[2]   Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays [J].
Alon, U ;
Barkai, N ;
Notterman, DA ;
Gish, K ;
Ybarra, S ;
Mack, D ;
Levine, AJ .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1999, 96 (12) :6745-6750
[3]   MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia [J].
Armstrong, SA ;
Staunton, JE ;
Silverman, LB ;
Pieters, R ;
de Boer, ML ;
Minden, MD ;
Sallan, SE ;
Lander, ES ;
Golub, TR ;
Korsmeyer, SJ .
NATURE GENETICS, 2002, 30 (01) :41-47
[4]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[5]   Microarray expression profiling identifies genes with altered expression in HDL-deficient mice [J].
Callow, MJ ;
Dudoit, S ;
Gong, EL ;
Speed, TP ;
Rubin, EM .
GENOME RESEARCH, 2000, 10 (12) :2022-2029
[6]   Combining mouse congenic strains and microarray gene expression analyses to study a complex trait: The NOD model of type 1 diabetes [J].
Eaves, IA ;
Wicker, LS ;
Ghandour, G ;
Lyons, PA ;
Peterson, LB ;
Todd, JA ;
Glynne, RJ .
GENOME RESEARCH, 2002, 12 (02) :232-243
[7]   Diversity of gene expression in adenocarcinoma of the lung [J].
Garber, ME ;
Troyanskaya, OG ;
Schluens, K ;
Petersen, S ;
Thaesler, Z ;
Pacyna-Gengelbach, M ;
van de Rijn, M ;
Rosen, GD ;
Perou, CM ;
Whyte, RI ;
Altman, RB ;
Brown, PO ;
Botstein, D ;
Petersen, I .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2001, 98 (24) :13784-13789
[8]   Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring [J].
Golub, TR ;
Slonim, DK ;
Tamayo, P ;
Huard, C ;
Gaasenbeek, M ;
Mesirov, JP ;
Coller, H ;
Loh, ML ;
Downing, JR ;
Caligiuri, MA ;
Bloomfield, CD ;
Lander, ES .
SCIENCE, 1999, 286 (5439) :531-537
[9]  
Gruvberger S, 2001, CANCER RES, V61, P5979
[10]   Gene-expression profiles in hereditary breast cancer. [J].
Hedenfalk, I ;
Duggan, D ;
Chen, YD ;
Radmacher, M ;
Bittner, M ;
Simon, R ;
Meltzer, P ;
Gusterson, B ;
Esteller, M ;
Kallioniemi, OP ;
Wilfond, B ;
Borg, Å ;
Trent, J ;
Raffeld, M ;
Yakhini, Z ;
Ben-Dor, A ;
Dougherty, E ;
Kononen, J ;
Bubendorf, L ;
Fehrle, W ;
Pittaluga, S ;
Gruvberger, S ;
Loman, N ;
Johannsoson, O ;
Olsson, H ;
Sauter, G .
NEW ENGLAND JOURNAL OF MEDICINE, 2001, 344 (08) :539-548