The effects of normalization on the correlation structure of microarray data

BMC Bioinformatics

Volumn 6, Issue , 2005, Pages

  Qiu, Xing ^a   Brooks, Andrew I ^a   Klebanov, Lev ^a,b   Yakovlev, Andrei ^a  

^a UNIVERSITY OF ROCHESTER   (United States)

^b CHARLES UNIVERSITY   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

CHILDHOOD LEUKEMIA; CORRELATION STRUCTURE; DIFFERENTIALLY EXPRESSED GENE; GENE EXPRESSION LEVELS; LONG RANGE CORRELATIONS; NORMALIZATION METHODS; STATISTICAL INFERENCE; STOCHASTIC DEPENDENCE;

GENE EXPRESSION;

STATISTICAL TESTS;

ARTICLE; CHILDHOOD LEUKEMIA; DNA MICROARRAY; GENE EXPRESSION; GENE INTERACTION; GENETIC CORRELATION; HUMAN; MATHEMATICAL COMPUTING; METHODOLOGY; SIMULATION; STATISTICAL ANALYSIS; ALGORITHM; ANALYSIS OF VARIANCE; BIOLOGICAL MODEL; BIOLOGY; COMPUTER PROGRAM; COMPUTER SIMULATION; CONFIDENCE INTERVAL; DNA SEQUENCE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; NONPARAMETRIC TEST; PROCEDURES; REPRODUCIBILITY; SEQUENCE ALIGNMENT; STATISTICAL MODEL; STATISTICS; THEORETICAL MODEL;

ALGORITHMS; ANALYSIS OF VARIANCE; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; CONFIDENCE INTERVALS; DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MODELS, GENETIC; MODELS, STATISTICAL; MODELS, THEORETICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, DNA; SOFTWARE; STATISTICS, NONPARAMETRIC; STOCHASTIC PROCESSES;

EID: 25444485444     PISSN: 14712105     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-6-120     Document Type: Article

References (23)

1. Efron B, Tibshirani R, Storey JD, Tusher V: Empirical Bayes analysis of a microarray experiment. J Amer Statist Assoc 2001, 96: 1151-1160.
2. Efron B: Robbins, empirical Bayes and microarrays. Ann Statist 2003, 31: 366-378.
3. Efron B: Large-scale simultaneous hypothesis testing: The choice of a null hypothesis. J Amer Statist Assoc 2004, 99: 96-104.
4. Newton MA, Kendziorski CM, Richmond CS, Blattner, FR, Tsui KW: On differential variability of expression ratios: Improving statistical inference about gene expression changes from microarray data. J of Comput Biol 2000, 8(1): 37-52.
5. Newton MA, Kendziorski CM: Parametric empirical Bayes methods for microarrays. In: The Analysis of Gene Expression Data, Parmigiani, G., Garrett, E.S., Irizarry, R.A., Zeger, S.L., eds, Springer, New York, 2003: 254-271.
6. McLachlan GJ, Do K-A, Ambroise, C: Analyzing Microarray Gene Expression Data. Wiley, New York, 2004.
7. Dalmasso C, Broet P, Moreau T: A simple procedure for estimating thye false discovery rate. Bioinformatics Advanced Access, 2004.
8. Broet P, Lewin A, Richardson S, Dalmasso C, Magdalenat H: A mixture model-based strategy for selecting genes in multiclass response microarray experiments. Bioinformatics 2004: 2562-2571.
9. Ideker T, Thorsson V, Seigel AF, Hood LE: Testing for differentially expressed genes by maximum likelihood analysis of microarray data. J Comput Biol 2000, 7(6): 805-817.
10. Segal E, Wang H, Koller D: Discovering molecular pathways from protein interactions and gene expression data. Bioinformatics 2003, 19: i264-i272.
11. Tsai C-A, Hsueh, H-M, Chen JJ: Estimation of false discovery rates in multiple testing: application to gene microarray data. Biometrics 2003, 59: 1071-1081.
12. Storey JD: Comment on 'Resampling-based multiple testing for DNA microarray data analysis' by Ge, Dudoit, and Speed. Test 2003, 12: 1-77.
13. Storey JD, Taylor JE, Siegmund D: Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach. J R Statist Soc B 2004, 66: 187-205.
14. Ge Y, Dudoit S, Speed TP: Resampling-based multiple testing for DNA microarray data analysis. TEST 2003, 12(1): 1-44.
15. D'haeseller P, Liang S, Somogyi R: Genetic network inference: from co-expression clustering to reverse engineering. Bioinformatics 2000, 16: 707-726.
16. Park T, Yi S-G, Kang S-H, Lee S-Y, Lee Y-S, Simon R: Evaluation of normalization methods for microarray data. BMC Bioinformatics 2003, 4:33.
17. Marshall E: Getting the noise out of gene arrays. Science 2004, 306: 630-631.
18. St. Jude Children's Research Hospital (SJCRH) Database on childhood leukemia [http://www.stjuderesearch.org/data/ALL1/]
19. Tsodikov A, Szabo A, Jones D: Adjustments and measures of differential expression for microarray data. Bioinformatics 2002, 18(2): 251-260.
20. Szabo A, Boucher K, Carroll W, Klebanov L, Tsodikov A, Yakovlev A: Variable selection and pattern recognition with gene expression data generated by the microarray technology. Mathematical Biosciences 2002, 176:71-98.
21. Bolstad BM, Irizarry RA, Astrand M, Speed TP: A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 2003, 19(2):185-193.
22. Simon, R.M., Korn, E.L., McShane, L.M., Radmacher, M.D., Wright, G.W., Zhao, Y. (2003). Design and Analysis of DNA Microarray Investigations, Springer, New York.
23. Irizarry RA, Gautier L, Cope LM: An R package for analyses of Affymetrix oligonucleotide arrays, In: The Analysis of Gene Expression Data 2003, Parmigiani G, Garrett ES, Irizarry RA, Zeger SL, eds, Springer, New York, pp. 102-119.