A new type of stochastic dependence revealed in gene expression data

Statistical Applications in Genetics and Molecular Biology

Volumn 5, Issue 1, 2006, Pages

  Klebanov, Lev ^a   Jordan, Craig ^b   Yakovlev, Andrei ^b  

^a CHARLES UNIVERSITY   (Czech Republic)

^b UNIVERSITY OF ROCHESTER   (United States)

Author keywords

Gene expression; Microarray analysis; Stochastic dependence

Indexed keywords

ARTICLE; BASE PAIRING; CHILDHOOD LEUKEMIA; GENE EXPRESSION; HUMAN; MATHEMATICAL COMPUTING; METHODOLOGY; MICROARRAY ANALYSIS; PHENOTYPIC VARIATION; STATISTICAL ANALYSIS; STOCHASTIC MODEL; CHILD; DNA MICROARRAY; EVALUATION; GENE EXPRESSION PROFILING; GENETICS; LYMPHATIC LEUKEMIA; METABOLISM; STATISTICS;

CHILD; GENE EXPRESSION PROFILING; HUMANS; LEUKEMIA, LYMPHOCYTIC; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; STOCHASTIC PROCESSES;

EID: 33646358230     PISSN: 15446115     EISSN: 15446115     Source Type: Journal    
DOI: 10.2202/1544-6115.1189     Document Type: Article

References (17)

1. Butte AJ, Tamayo P, Slonim D, Golub TR (2000) Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks. Proc Natl Acad Sci USA 97, 12182-12186.
2. Dettling M, Gabrielson E, Parmigiani G (2005) Searching for differentially expressed gene combinations. Genome Biology 6, R88.
3. Dudoit S, Shaffer JP, and Boldrick JC (2003) Multiple hypothesis testing in microarray experiments. Statistical Science 18, 71-103.
4. Efron B (2005) Correlation and large-scale simultaneous significance testing. http://www-stat.stanford.edu/brad/papers
5. Efron B, Tibshirani R (1993) An Introduction to the Bootstrap, Chapman & Hall/CRC, New York.
6. Goerman JJ, van de Geer SA, de Kort F, van Houwelingen HC (2004) A global test for groups of genes: testing association with a clinical outcome. Bioinformatics 20, 93-99.
7. Jaeger J, Sengupta R, Ruzzo WL (2003) Improved gene selection for classification of microarrays. Pacific Symposium on Biocomputing, Kauai, HI, 53-64.
8. Klebanov L, Gordon A, Xiao Y, Land H, Yakovlev A (2005) A permutation test motivated by microarray data analysis. Comp Stat Data Anal, in press
9. Lee M-LT, Gray RJ, Björkbacka H, Freeman MW (2005) Generalized rank tests for replicated microarray data. Stat Appl Genet Mol Biol, 4: # 3
10. 2 multivariate profiling for detecting differential expression in microarrays. Bioinformatics 21, 3105-3113.
11. Politis DN, Romano JP (1994) Large sample confidence regions based on subsamples under minimal assumptions. Ann Statist 22, 2031-2050.
12. Qiu X, Brooks AI, Klebanov L, Yakovlev A (2005a) The effects of normalization on the correlation structure of microarray data. BMC Bioinformatics 6: # 120
13. Qiu X, Klebanov L, Yakovlev AY (2005b) Correlation between gene expression levels and limitations of the empirical Bayes methodology for finding differentially expressed genes. Statistical Applications in Genetics and Molecular Biology, 4, Article 34.
14. Shao J, Tu D (1995) The Jackknife and Bootstrap. Springer Series in Statistics, Springer, NY
15. Storey JD, Tibshirani R (2003) Statistical significance for genomewide studies. Proc Natl Acad Sci USA 100: 9440-9445
16. Storey JD, Taylor JE, Siegmund D (2004) Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach. J R Statist Soc B 66, 187-205.
17. Xiao Y, Frisina R, Gordon A, Klebanov L, Yakovlev A (2004) Multivariate search for differentially expressed gene combinations. BMC Bioinformatics 5: # 164