Bioinformatics Vol. 18 no. 9 2002
Pages 1184-1193
© 2002 Oxford University Press
Determination of minimum sample size and discriminatory expression patterns in microarray data
1 Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Received on August 3, 2001
; revised on December 20, 2001
; accepted on March 26, 2002
Motivation: Transcriptional profiling using microarrays can reveal important information about cellular and tissue expression phenotypes, but these measurements are costly and time consuming. Additionally, tissue sample availability poses further constraints on the number of arrays that can be analyzed in connection with a particular disease or state of interest. It is therefore important to provide a method for the determination of the minimum number of microarrays required to separate, with statistical reliability, distinct disease states or other physiological differences.
Results: Power analysis was applied to estimate the minimum sample size required for two-class and multi-class discrimination. The power analysis algorithm calculates the appropriate sample size for discrimination of phenotypic subtypes in a reduced dimensional space obtained by Fisher discriminant analysis (FDA). This approach was tested by applying the algorithm to existing data sets for estimation of the minimum sample size required for drawing certain conclusions on multi-class distinction with statistical reliability. It was confirmed that when the minimum number of samples estimated from power analysis is used, group means in the FDA discrimination space are statistically different.
Contact: gregstep{at}mit.edu
* To whom correspondence should be addressed.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  P. de Valpine, H.-M. Bitter, M. P. S. Brown, and J. Heller A simulation-approximation approach to sample size planning for high-dimensional classification studies Biostat., July 1, 2009; 10(3): 424 - 435. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. Liu and J. T. G. Hwang Quick calculation for sample size while controlling false discovery rate with application to microarray analysis Bioinformatics, March 15, 2007; 23(6): 739 - 746. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. K. Dobbin and R. M. Simon Sample size planning for developing classifiers using high-dimensional DNA microarray data Biostat., January 1, 2007; 8(1): 101 - 117. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J Tian, K Ishibashi, S Honda, S A Boylan, L M Hjelmeland, and J T Handa The expression of native and cultured human retinal pigment epithelial cells grown in different culture conditions Br. J. Ophthalmol., November 1, 2005; 89(11): 1510 - 1517. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. G. Giresi, E. J. Stevenson, J. Theilhaber, A. Koncarevic, J. Parkington, R. A. Fielding, and S. C. Kandarian Identification of a molecular signature of sarcopenia Physiol Genomics, April 14, 2005; 21(2): 253 - 263. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. Pusztai and K. R. Hess Clinical trial design for microarray predictive marker discovery and assessment Ann. Onc., December 1, 2004; 15(12): 1731 - 1737. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 N. Le Meur, G. Lamirault, A. Bihouee, M. Steenman, H. Bedrine-Ferran, R. Teusan, G. Ramstein, and J. J. Leger A dynamic, web-accessible resource to process raw microarray scan data into consolidated gene expression values: importance of replication Nucleic Acids Res., October 8, 2004; 32(18): 5349 - 5358. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. Ishibashi, J. Tian, and J. T. Handa Similarity of mRNA Phenotypes of Morphologically Normal Macular and Peripheral Retinal Pigment Epithelial Cells in Older Human Eyes Invest. Ophthalmol. Vis. Sci., September 1, 2004; 45(9): 3291 - 3301. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Ayers, W.F. Symmans, J. Stec, A.I. Damokosh, E. Clark, K. Hess, M. Lecocke, J. Metivier, D. Booser, N. Ibrahim, et al. Gene Expression Profiles Predict Complete Pathologic Response to Neoadjuvant Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide Chemotherapy in Breast Cancer J. Clin. Oncol., June 15, 2004; 22(12): 2284 - 2293. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Tian, K. Ishibashi, and J. T. Handa The expression of native and cultured RPE grown on different matrices Physiol Genomics, April 13, 2004; 17(2): 170 - 182. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
O. Tarnavski, J. R. McMullen, M. Schinke, Q. Nie, S. Kong, and S. Izumo Mouse cardiac surgery: comprehensive techniques for the generation of mouse models of human diseases and their application for genomic studies Physiol Genomics, February 13, 2004; 16(3): 349 - 360. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Dangond, D. Hwang, S. Camelo, P. Pasinelli, M. P. Frosch, G. Stephanopoulos, G. Stephanopoulos, R. H. Brown Jr., and S. R. Gullans Molecular signature of late-stage human ALS revealed by expression profiling of postmortem spinal cord gray matter Physiol Genomics, January 15, 2004; 16(2): 229 - 239. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. C. K. Yang, J. J. Yang, R. A. McIndoe, and J. X. She Microarray experimental design: power and sample size considerations Physiol Genomics, December 16, 2003; 16(1): 24 - 28. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. Pellis, N. L. W. Franssen-van Hal, J. Burema, and J. Keijer The intraclass correlation coefficient applied for evaluation of data correction, labeling methods, and rectal biopsy sampling in DNA microarray experiments Physiol Genomics, December 16, 2003; 16(1): 99 - 106. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. Pusztai, M. Ayers, J. Stec, and G. N. Hortobagyi Clinical Application of cDNA Microarrays in Oncology Oncologist, June 1, 2003; 8(3): 252 - 258. [Abstract] [Full Text] [PDF]
|
|