Spearman's footrule as a measure of cDNA microarray reproducibility

Genomics

Volumn 84, Issue 2, 2004, Pages 441-448

  Kim, Byung Soo ^a   Rha, Sun Young ^b   Cho, Ga Bee ^b   Chung, Hyun Cheol ^b  

^a Yonsei University   (South Korea)

^b Yonsei University College of Medicine   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEMENTARY DNA; MESSENGER RNA;

ANALYTIC METHOD; ARTICLE; CONTROLLED STUDY; CORRELATION ANALYSIS; DATA ANALYSIS; DNA MICROARRAY; GENE REPLICATION; HUMAN; HUMAN CELL; HYBRIDIZATION; PRIORITY JOURNAL; REPRODUCIBILITY; VALIDATION PROCESS;

EID: 3042513378     PISSN: 08887543     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ygeno.2004.02.015     Document Type: Review

References (17)

1. Schena M., Shalon D., Davis R.W., Brown P.O. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 270:1995;368-369
2. Gibson G. Microarray in ecology and evolution: a preview. Mol. Ecol. 11:2002;17-24
3. Yang Y.H., Speed T. Design and analysis of comparative microarray experiments. Speed T. Statistical Analysis of Gene Expression Microarray Data. 2003;35-91 Springer, New York
4. Jin W., et al. The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat. Genet. 29:2001;389-395
5. Lee M.-L.T., Kuo F.C., Whitmore G.A., Sklar J. Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive DNA hybridization. Proc. Natl. Acad. Sci. USA. 97:2000;9834-9839
6. Tseng G.C., Oh M.-K., Rohlin L., Liao J.C., Wong W.H. Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects. Nucleic Acids Res. 29:2001;2549-2557
7. Churchill G.A. Fundamentals of experimental design for cDNA microarrays. Nat. Genet. Suppl. 32:2002;490-495
8. Kerr M.K. Design considerations for efficient and effective microarray studies. Biometrics. 59:2003;822-828
9. Yue H., et al. An evaluation of the performance of cDNA microarrays for detecting changes in global RNA expression. Nucleic Acids Res. 28:2001;e41
10. Kerr M.K., Martin M., Churchill G.A. Analysis of variance for gene expression microarray data. J. Comp. Biol. 7:2000;819-837
11. Kendall M. Rank Correlation Methods. 4th edition:1970;Griffin, London
12. Dwork C., Kumar R., Naor M., Sivakumar D. Rank aggregation methods for the web. 2001;ACM, HongKong. http://www10.org/cdrom/papers/577
13. Diaconis P., Graham R.L. Spearman's footrule as a measure of disarray. J. R. Stat. Soc. B. 39:1977;262-268
14. Cheng C., Kimmel R., Neiman P., Zhao L.P. Array rank order regression analysis for the detection of gene copy-number changes in human cancer. Genomics. 82:2003;122-229
15. Veltman J.A., et al. Array-based comparative genomic hybridization for genome-wide screening of DNA copy number in bladder tumors. Cancer Res. 63:2003;2872-2880
16. Vasselli J.R., et al. Predicting survival in patients with metastatic kidney cancer by gene-expression profiling in the primary tumor. Proc. Natl. Acad. Sci. USA. 100:2003;6958-6963
17. Johnson N.L., Kotz S. Distributions in Statistics: Continuous Univariate Distributions-2. 1970;Wiley, New York