Identifying differentially expressed genes in time-course microarray experiment without replicate

Journal of Bioinformatics and Computational Biology

Volumn 5, Issue 2 A, 2007, Pages 281-296

  Han, Xu ^a   Sung, Wing Kin ^a,b   Feng, Lin ^c  

^a GENOME INSTITUTE OF SINGAPORE   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Differentially expressed gene; PEM; Time course microarray experiment

Indexed keywords

COMPLEMENTARY DNA;

CELL CYCLE; CLUSTER ANALYSIS; COMPUTER PROGRAM; CONFERENCE PAPER; DNA MICROARRAY; ENVIRONMENTAL STRESS; EVOLUTIONARY ADAPTATION; FOURIER TRANSFORMATION; GENE EXPRESSION PROFILING; GENE IDENTIFICATION; GENETIC ALGORITHM; KAPPA STATISTICS; MATHEMATICAL COMPUTING; NONHUMAN; NORMAL DISTRIBUTION; RECEIVER OPERATING CHARACTERISTIC; REGRESSION ANALYSIS; REPRODUCIBILITY; SACCHAROMYCES CEREVISIAE; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; SIGNAL NOISE RATIO; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL SIGNIFICANCE; TIME SERIES ANALYSIS;

EID: 34347389249     PISSN: 02197200     EISSN: None     Source Type: Journal    
DOI: 10.1142/s0219720007002655     Document Type: Conference Paper

References (19)

1. Lönnstedt I, Speed TP, Replicated microarray data, Statistica Sinica 12:31-46, 2002.
2. Park T, Yi S, Lee S, Lee SY, Yoo D, Ahn J, Lee Y, Statistical tests for identifying differentially expressed genes in time-course microarray experiments, Bioinform 19:694-703, 2003.
3. Smyth GK, Linear models and empirical bayes methods for assessing differential expression in microarray experiments, Statistical Appl Gene and Mole Biol 3: Article 3, 2004.
4. Guo X, Qi H, Verfaillie CM, Pan W, Statistical significance analysis of longitudinal gene expression data, Bioinform 19:1628-1635, 2003.
5. Storey JD, Xiao W, Leek JT, Tompkins RG, Davis RW, Significance analysis of time course microarray experiments, Proc Natl Acad Sci 102 12837-12842, 2005.
6. Eisen MB, Spellman PT, Brown PO, Botstein D, Cluster analysis and display of genome-wide expression patterns, Proc Natl Acad Sci 95:14863-14868, 1998.
7. Bar-Joseph Z, Gerber G, Simon I, Gifford D, Jaakkola T, Comparing the continuous representation of time-series expression profiles to identify differentially expressed genes, Proc Natl Acad Sci 100 10146-10151, 2003.
8. Spellman PT, Sherlock G, Zhang MO, Iyer VR, Anders K, Eisen MB, Brown PO, Botstein D, Futcher B, Comprehensive identification of cell-cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization, Mol Biol Cell 9:3273-3297, 1998.
9. Peddada SD, Lobenhofer EK, Li L, Afshari CA, Weinberg CR, Umbach DM, Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference, Bioinform 19:834-841, 2003.
10. Xu XL, Olson JM, Zhao LP, A regression-based method to identify differentially expressed genes in microarray time course studies and its application in an inducible Huntington's disease transgenic model, Human Molecular Genetics 11:1977-1985, 2002.
11. Tusher V, Tibshirani R, Chu G, Significance analysis of microarrays applied to the ionizing radiation response, Proc Natl Acad Sci 98:5116-5121, 2001.
12. Bar-Joseph Z, Gerber G, Gifford D, Jaakkola T, Simon I, A new approach to analyzing gene expression time series data, RECOMB 39-48, 2002.
13. Benjamini Y, Hochberg Y, Controlling the false discovery rate: A practical and powerful approach to multiple testing, J Roy Stat Soc B 57:289-300, 1995.
14. Gasch AP, Spellman PT, Kao CM, Carmel-Harel O, Eisen MB, Storz G, Botstein D, Brown PO, Genomic expression programs in the response of yeast cells to environmental changes, Mol Biol Cell 11 4241-4257, 2000.
15. Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP, Normalization for cDNA microarray data: A robust composite method addressing single and multiple slide systematic variation, Nucleic Acids Res 30:e15, 2002.
16. Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB, Missing value estimation methods for DNA microarrays, Bioinform 17:520-525, 2001.
17. McNeil BJ, Hanley JA, Statistical approaches to the analysis of receiver operating characteristic (ROC) curves, Med Decis Mak 4 137-150, 1984.
18. DeRisi JL, Iyer VR, Brown PO, Exploring the metabolic and genetic control of gene expression on a genomic scale, Science 278 680-686, 1997.
19. Chen D, Toone WM, Mata J, Lyne R, Burns G, Kivinen K, Brazma A, Jones N, Bähler J, Global transcriptional responses of fission yeast to environmental stress, Mol Biol Cell 14:214-229, 2003.