Systematic variation normalization in microarray data to get gene expression comparison unbiased

Journal of Bioinformatics and Computational Biology

Volumn 3, Issue 2, 2005, Pages 225-241

  Chou, Jeff W ^a   Paules, Richard S ^a   Bushel, Pierre R ^a,b  

^a NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES   (United States)

^b NORTH CAROLINA STATE UNIVERSITY   (United States)

Author keywords

Gene expression; Microarray; Normalization; Statistics; Systematic variation

Indexed keywords

ARTICLE; DNA MICROARRAY; GENE EXPRESSION; GENETIC VARIABILITY; LINEAR REGRESSION ANALYSIS; MATHEMATICAL COMPUTING; NONLINEAR REGRESSION ANALYSIS; STATISTICAL DISTRIBUTION; STATISTICS;

ALGORITHMS; CALIBRATION; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION PROFILING; MODELS, GENETIC; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; VARIATION (GENETICS);

EID: 17644398746     PISSN: 02197200     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219720005001028     Document Type: Article

References (20)

1. Richmond T, Somerville S, Chasing the dream: Plant EST microarray, Curr Opini Plant Biol 3:108-116, 2000.
2. Schuchhardt J, Beule D, Malik A, Wolski E, Eickhoff H, Lehrach H, Herzel H, Normalization strategies for cDNA microarrays, Nucleic Acid Res 28:e47, 2000.
3. Quackenbush J, Microarray data normalization and transformation, Nature Genet Suppl 32:496-501, 2002.
4. Cleveland WS, Robust locally weighted regression and smoothing scatterplots, J Amer Stat Assoc 74:829-836, 1979.
5. Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, TP, Normalization for cDNA microarray data: A robust composite method addressing single and multiple slide systematic variation, Nucleic Acid Res 30 e15 2002.
6. Workman C, Jensen LJ, Jarmer H, Berka R, Gautier L, Nielsen HB, Saxild H, Nielson C, Brunak S, Knudsen S, A new non-linear normalization method for reducing variability in DNA microarray experiments, Genome Biol 3:1-16, 2002.
7. Kepler TB, Crosby L, Torgan KT, Normalization and analysis of DNA microarray data by self-consistence and local regression, Genome Biol 3:1-12, 2002.
8. Finkelstein D, Ewing R, Gollub J, Sterky F, Cherry M, Somerville S, Microarray data quality analysis: Lessons from the AFGC project, Plant Mol Biol 48:119-131, 2002.
9. Schena M, Shalon D, Davis RW, Brown PO, Quantitative monitoring of gene expression patterns with complementary DNA microarray, Science 170:467-470, 1995.
10. Hughes TR, Marton MJ, Jones AR, Roberts CJ, Stoughton R, Armour CD, Bennett HA, Coffey E, Dai H, He YD, Kidd MJ, King AM, Meyer MR, Slade D, Lum PY, Stepaniants SB, Shoemaker DD, Gachotte D, Chakraburtty K, Simon J, Bard M, Friend SH, Functional discovery via a compendium of expression profiles, Cell 102:109-126, 2000.
11. Chen Y, Dougherty ER, Bittner ML, Ratio-based decisions and the quantitative analysis of cDNA microarray images, J Biomed Optics 2:364-374, 1997.
12. Hamadeh HK, Knight BL, Haugen AC, Sieber S, Amin RP, Bushel PR, Stoll R, Blanchard K, Jayadev S, Tennant RW, Cunningham ML, Afshari CA, Paules RS, Methapyrilene toxicity: Anchorage of pathologic observations to gene expression alterations, Toxicol Pathol 30:470-482, 2002.
13. Camerer E, Gjernes E, Wiiger M, Pringle S, Prydz H, Binding of factor VIIa to tissue factor on keratinocytes induces gene expression, J Biol Chem 275:6580-6585, 2000.
14. Yu Z, Ford BN, Glickman BW, Identification of genes responsive to BPDE treatment in Hela cells using cDNA expression assays, Environ Mol Mutage 36:201-205, 2000.
15. Tseng GC, Oh MK, Rohlin L, Liao JC, Wong WH, Issues in cDNA microarray analysis: Quality filtering, channel normalization, models of variations and assessment of gene effects, Nucleic Acid Res 29 2549-2557, 2001.
16. Hill AA, Brown EL, Whiteley MZ, Tucker-Kellogg G, Hunter CP, Slonim DK, Evaluation of normalization procedures for oligonucleotide array data based on spiked cRNA controls, Genomebiol 2:1-13, 2001.
17. Welsh JB, Sapinoso LM, Su AI, Kern SG, Wang-Rodriguez J, Moskaluk CA, Frierson HF Jr, Hampton GM, Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer, Cancer Res 61:439-442, 2001.
18. Bevington PR, in Data Reduction and Error Analysis for the Physical Sciences, Chapter 2, McGraw-Hill, New York, 1969.
19. Heydebreck Av, Huber W, Poustka A, Vingron M, Proceedings in Computational Statistics (COMPSTAT), pp. 623-628, Physica Verlag, 2002.
20. 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 19:185-193, 2003.