An evaluation framework for statistical tests on microarray data

Dondrup M, Hueser AT, Mertens D, Goesmann A (2009)
JOURNAL OF BIOTECHNOLOGY 140(1-2): 18-26.

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Zeitschriftenaufsatz | Veröffentlicht | Englisch
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Abstract / Bemerkung
Microarray analysis has become a popular and routine method in functional genomics. It is typical for such experiments to involve a small number of replicates, which causes Unreliable estimates of the sample variance. Microarrays have fostered the development of new statistical methods to analyze data resulting from experiments with small sample sizes. In this study, we tackle the problem of evaluating the performance of statistical tests for generating ranked gene lists from two-channel direct comparisons. We propose all evaluation method based oil a oligonucleotide microarray with a large number of replicate spots yielding a maximum) of 400 replicates per gene. We apply Spearman's rank correlation coefficient to ranked gene-lists generated by eight widely used microarray specific test statistics, which are applied to small random samples. We could show that variance stabilizing methods such as Cyber-T, SAM, and LIMMA can he beneficial for very small sample sizes and that SAM and the t-test provide stronger control of the type I error rate than the other methods. Specifically, we report that for four replicates all methods to very high correlation with our reference standard. (C) 2009 Elsevier B.V. All rights reserved.
Erscheinungsjahr
Zeitschriftentitel
JOURNAL OF BIOTECHNOLOGY
Band
140
Zeitschriftennummer
1-2
Seite
18-26
ISSN
PUB-ID

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Dondrup M, Hueser AT, Mertens D, Goesmann A. An evaluation framework for statistical tests on microarray data. JOURNAL OF BIOTECHNOLOGY. 2009;140(1-2):18-26.
Dondrup, M., Hueser, A. T., Mertens, D., & Goesmann, A. (2009). An evaluation framework for statistical tests on microarray data. JOURNAL OF BIOTECHNOLOGY, 140(1-2), 18-26. doi:10.1016/j.jbiotec.2009.01.009
Dondrup, M., Hueser, A. T., Mertens, D., and Goesmann, A. (2009). An evaluation framework for statistical tests on microarray data. JOURNAL OF BIOTECHNOLOGY 140, 18-26.
Dondrup, M., et al., 2009. An evaluation framework for statistical tests on microarray data. JOURNAL OF BIOTECHNOLOGY, 140(1-2), p 18-26.
M. Dondrup, et al., “An evaluation framework for statistical tests on microarray data”, JOURNAL OF BIOTECHNOLOGY, vol. 140, 2009, pp. 18-26.
Dondrup, M., Hueser, A.T., Mertens, D., Goesmann, A.: An evaluation framework for statistical tests on microarray data. JOURNAL OF BIOTECHNOLOGY. 140, 18-26 (2009).
Dondrup, Michael, Hueser, Andrea T., Mertens, Dominik, and Goesmann, Alexander. “An evaluation framework for statistical tests on microarray data”. JOURNAL OF BIOTECHNOLOGY 140.1-2 (2009): 18-26.

6 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Altered integrin expression patterns shown by microarray in human cutaneous melanoma.
Vizkeleti L, Kiss T, Koroknai V, Ecsedi S, Papp O, Szasz I, Adany R, Balazs M., Melanoma Res 27(3), 2017
PMID: 28234767
Cyber-T web server: differential analysis of high-throughput data.
Kayala MA, Baldi P., Nucleic Acids Res 40(web server issue), 2012
PMID: 22600740
Construction and evaluation of a whole genome microarray of Chlamydomonas reinhardtii.
Toepel J, Albaum SP, Arvidsson S, Goesmann A, la Russa M, Rogge K, Kruse O., BMC Genomics 12(), 2011
PMID: 22118351
The Zur regulon of Corynebacterium glutamicum ATCC 13032.
Schröder J, Jochmann N, Rodionov DA, Tauch A., BMC Genomics 11(), 2010
PMID: 20055984
Genome profiles in maternal blood during early onset preeclampsia and towards term.
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PMID: 20807010

34 References

Daten bereitgestellt von Europe PubMed Central.

Microarray data analysis: from disarray to consolidation and consensus.
Allison DB, Cui X, Page GP, Sabripour M., Nat. Rev. Genet. 7(1), 2006
PMID: 16369572

AUTHOR UNKNOWN, 0
Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments
Dudoit, Stat. Sin. 12(), 2002
Multiplexed biochemical assays with biological chips.
Fodor SP, Rava RP, Huang XC, Pease AC, Holmes CP, Adams CL., Nature 364(6437), 1993
PMID: 7687751
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES., Science 286(5439), 1999
PMID: 10521349
Functional discovery via a compendium of expression profiles.
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., Cell 102(1), 2000
PMID: 10929718
GEST: a gene expression search tool based on a novel Bayesian similarity metric.
Hunter L, Taylor RC, Leach SM, Simon R., Bioinformatics 17 Suppl 1(), 2001
PMID: 11473000
Development of a Corynebacterium glutamicum DNA microarray and validation by genome-wide expression profiling during growth with propionate as carbon source
Hüser, J. Biotechnol. 106(2–3), 2003
Replicated microarray data
Lönnstedt, Stat. Sin. 12(), 2002
The effect of replication on gene expression microarray experiments.
Pavlidis P, Li Q, Noble WS., Bioinformatics 19(13), 2003
PMID: 12967957

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
Moderated statistical tests for assessing differences in tag abundance.
Robinson MD, Smyth GK., Bioinformatics 23(21), 2007
PMID: 17881408
Functional genomics and expression analysis of the Corynebacterium glutamicum fpr2-cysIXHDNYZ gene cluster involved in assimilatory sulphate reduction.
Ruckert C, Koch DJ, Rey DA, Albersmeier A, Mormann S, Puhler A, Kalinowski J., BMC Genomics 6(), 2005
PMID: 16159395
Quantitative monitoring of gene expression patterns with a complementary DNA microarray.
Schena M, Shalon D, Davis RW, Brown PO., Science 270(5235), 1995
PMID: 7569999
An analysis of variance test for normality (complete samples)
Shapiro, Biometrica 52(), 1965

Siegel, 1956
Linear models and empirical bayes methods for assessing differential expression in microarray experiments
Smyth, Stat. Appl. Genet. Mol. Biol. 3(), 2004
Nonparametric methods for identifying differentially expressed genes in microarray data.
Troyanskaya OG, Garber ME, Brown PO, Botstein D, Altman RB., Bioinformatics 18(11), 2002
PMID: 12424116
Significance analysis of microarrays applied to the ionizing radiation response.
Tusher VG, Tibshirani R, Chu G., Proc. Natl. Acad. Sci. U.S.A. 98(9), 2001
PMID: 11309499
Serial analysis of gene expression.
Velculescu VE, Zhang L, Vogelstein B, Kinzler KW., Science 270(5235), 1995
PMID: 7570003
RNA-seq: a revolutionary tool for transcriptomics
Wang, Nat. Rev. Genet. (November), 2008
Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.
Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP., Nucleic Acids Res. 30(4), 2002
PMID: 11842121
Design issues for cDNA microarray experiments.
Yang YH, Speed T., Nat. Rev. Genet. 3(8), 2002
PMID: 12154381

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