Statistical implications of pooling RNA samples for microarray experiments

BMC Bioinformatics

Volumn 4, Issue , 2003, Pages

  Peng, Xuejun ^a   Wood, Constance L ^a   Blalock, Eric M ^a   Chen, Kuey Chu ^a   Landfield, Philip W ^a   Stromberg, Arnold J ^a  

^a UNIVERSITY OF KENTUCKY   (United States)

Author keywords

Microarray experiment design; Pooling; Power; Replicates; Sample size estimation

Indexed keywords

RNA;

ANALYTICAL ERROR; ARTICLE; COMPUTER SIMULATION; CONTROLLED STUDY; COST CONTROL; COST EFFECTIVENESS ANALYSIS; FINANCIAL MANAGEMENT; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENETIC VARIABILITY; HUMAN; INFORMATION PROCESSING; MATHEMATICAL COMPUTING; METHODOLOGY; MODEL; MOLECULAR BIOLOGY; MOUSE; NONHUMAN; PROTEIN MICROARRAY; RAT; RNA ANALYSIS; SAMPLE SIZE; STATISTICAL ANALYSIS; BIOLOGY; DNA MICROARRAY; ECONOMICS; EMPIRICAL RESEARCH; GENETICS; PILOT STUDY; STATISTICAL MODEL; STATISTICS;

COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; EMPIRICAL RESEARCH; GENE EXPRESSION PROFILING; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PILOT PROJECTS; RESEARCH DESIGN; RNA; SAMPLE SIZE;

EID: 0347621463     PISSN: 14712105     EISSN: None     Source Type: Journal    
DOI: 10.1186/1471-2105-4-26     Document Type: Article

References (16)

1. Lee MLT, Kuo FC, Whitmore GA and Sklar J: Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations Proc Nat Acad Sci 2000, 97:9834-9839.
2. Blalock EM, Chen KC, Sharrow K, Foster TC and Landfield PW: Gene microarray analyses of hippocampal aging: statistical profiling reveals novel expression programs correlated with cognitive impairment Journal of Neuroscience 2003, 23:3807-3819.
3. Pletcher SD, Macdonald SJ, Marguerie R, Certa U, Stearens SC, Goldstein DB and Partridge L: Genome-wide transcript Profiles in aging and calorically restricted drosophila melanogaster Current Biology 2002, 12:712-723.
4. Miller RA, Galecki A and Shmookler-Reis RJ: Interpretation, design, and analysis of gene array expression experiments J of Gerontol A Biol Sci Med Sci 2001, 56:B52-57.
5. Agrawal D, Chen T, Irby R, Quackenbush J, Chambers AF, Szabo M, Cantor A, Coppola D and Yeatman TJ: Osteopontin identified as a lead marker of colon cancer progression, using pooled sample expression profiling J Natl Cancer Inst 2002, 94(7):513-521.
6. Pan W, Lin J and Le CT: How many replicates of arrays are required to detect gene expression changes in microarray experiments? A mixture model approach Genome Biol 2002, 3(5):research0022.
7. GeneSpring: [http://www.silicongenetics.com]
8. Clontech: . http://www.clontech.com/ techinfo/manuals/ AtlasNavHelp/GlobalErrorModel.shtml, http://www.clontech.com/techinfo/manuals
9. Rocke DM and Lorenzato S: A two-component model for measurement error in analytical chemistry Technometrics 1995,37(2):176-185.
10. Durbin BP, Hardin JS, Hawkins DM and Rocke DM: A variance-stabilizing transformation for gene-expression microarray data Bioinformatics 2002, 18(Suppl 1):S105-S110.
11. Nadon R and Shoemaker J: Statistical issues with microarrays: processing and analysis Trends Genet 2002, 18(5):265-271.
12. Bakay M, Chen YW, Borup R, Zhao P, Nagaraju K and Hoffman E: Sources of variability and effect of experimental approach on expression profiling data interpretation BMC Bioinformatics 2002, 3:4.
13. Welle S, Brooks AI and Thornton CA: Computational methods for reducing variance with Affymetrix microarrays BMC Bioinformatics 2002, 3:23.
14. Casella G and Berger RL: Statistical Inference 2nd Edition. Duxbury Press; 2002.
15. Snedecor GW and Cochran WG: Statistical Methods 8th Edition. Iowa University Press; 1989.
16. Douglas C: Montgomery: Design and Analysis of Experiments 5th Edition.John Willy & Sons; 2000.