Best practices for hybridization design in two-colour microarray analysis

Trends in Biotechnology

Volumn 27, Issue 7, 2009, Pages 406-414

  Knapen, Dries ^a   Vergauwen, Lucia ^a   Laukens, Kris ^a   Blust, Ronny ^a  

^a UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

BEST PRACTICE; CURRENT TRENDS; DIFFERENTIALLY EXPRESSED GENE; EXPERIMENTAL SETUP; MICROARRAY ANALYSIS; POPULAR PLATFORM; TECHNICAL NOISE;

GENE EXPRESSION; MICROARRAYS;

DESIGN;

COMPLEMENTARY DNA; DYE; MESSENGER RNA;

BIOTECHNOLOGY; GENE EXPRESSION PROFILING; HUMAN; HYBRIDIZATION; INTERMETHOD COMPARISON; MICROARRAY ANALYSIS; MOLECULAR PROBE; NONHUMAN; NUCLEIC ACID HYBRIDIZATION; PRACTICE GUIDELINE; PREDICTION; PRIORITY JOURNAL; PROCESS OPTIMIZATION; RELIABILITY; REVIEW; TRANSCRIPTOMICS; TREND STUDY;

COLOR; NUCLEIC ACID HYBRIDIZATION; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; STAINING AND LABELING;

EID: 67549090128     PISSN: 01677799     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tibtech.2009.03.007     Document Type: Review

References (70)

1. Forster T., et al. Triple-target microarray experiments: a novel experimental strategy. BMC Genomics (2004) 5. http://www.biomedcentral.com 10.1186/1471-2164-5-13
2. Altman N.S., and Huan J. Extending the loop design for two-channel microarray experiments. Genet. Res. 88 (2006) 153-163
3. Dobbin K., et al. Statistical design of reverse dye microarrays. Bioinformatics 19 (2003) 803-810
4. Yang Y.H., and Speed T. Design issues for cDNA microarray experiments. Nat. Rev. Genet. 3 (2002) 579-588
5. Dobbin K., and Simon R. Comparison of microarray designs for class comparison and class discovery. Bioinformatics 18 (2002) 1438-1445
6. Golub T.R., and Slonim D.K. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286 (1999) 531-537
7. Dobbin K.K., and Simon R.M. Chapter 2: The statistical design and interpretation of microarray experiments. In: Gordon G.J. (Ed). Cancer Drug Discovery and Development: Bioinformatics in Cancer and Cancer Therapy (2008), Humana Press 13-23
8. Simon R., et al. Design of studies using DNA microarrays. Genet. Epidemiol. 23 (2002) 21-36
9. Churchill G.A. Fundamentals of experimental design for cDNA microarrays. Nat. Genet. 32 (2002) 490-495
10. Dombkowski A.A., et al. Gene-specific dye bias in microarray reference designs. FEBS Lett. 560 (2004) 120-124
11. Kerr M.K., et al. Statistical analysis of a gene expression microarray experiment with replication. Statist. Sinica 12 (2002) 203-217
12. Rosenzweig B.A., et al. Dye-bias correction in dual-labeled cDNA microarray gene expression measurements. Environ. Health Perspect. 112 (2004) 480-487
13. Dobbin K.K., et al. Characterizing dye bias in microarray experiments. Bioinformatics 21 (2005) 2430-2437
14. Smyth G.K., et al. Statistical issues in cDNA microarray. Methods Mol. Biol. 224 (2003) 111-136
15. Yang Y.H., et al. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30 (2002) e15
16. Kerr M.K., and Churchill G.A. Experimental design for gene expression microarrays. Biostatistics 2 (2001) 183-201
17. Kerr M.K., and Churchill G.A. Statistical design and the analysis of gene expression microarray data. Genet. Res. 89 (2001) 509-514
18. Glonek G.F., and Solomon P.J. Factorial and time course designs for cDNA microarray experiments. Biostatistics 5 (2004) 89-111
19. Landgrebe J., et al. Efficient design and analysis of two colour factorial microarray experiments. Comput. Stat. Data Anal. 50 (2006) 499-517
20. Wit E., et al. Near-optimal designs for dual channel microarray studies. Appl. Stat.-J. Roy. St. C 54 (2005) 817-830
21. Kerr M.K. Design considerations for efficient and effective microarray studies. Biometrics 59 (2003) 822-828
22. Nguyen N.K., and Williams E.R. Experimental designs for 2-colour cDNA microarray experiments. Appl. Stoch. Model Bus. 22 (2006) 631-638
23. Kerr M.K., and Churchill G.A. Bootstrapping cluster analysis: assessing the reliability of conclusions from microarray experiments. Proc. Natl. Acad. Sci. U. S. A. 98 (2001) 8961-8965
24. Martin-Magniette M.L., et al. Evaluation of the gene-specific dye bias in cDNA microarray experiments. Bioinformatics 21 (2005) 1995-2000
25. Dobbin K.K., et al. Comment on 'Evaluation of the gene-specific dye bias in cDNA microarray experiments'. Bioinformatics 21 (2005) 2803-2804
26. Ness S.A. Microarray analysis: basic strategies for successful experiments. Mol. Biotechnol. 36 (2007) 205-219
27. Speed T.P., and Yang Y.H. Direct versus indirect designs for cDNA microarray experiments. Sankhya Ser. A 64 (2002) 706-720
28. Yang Y.H., and Speed T. An introduction to microarray bioinformatics, part 1: design of microarray expression experiments. In: Bowtell D., and Sambrook J. (Eds). DNA Microarrays, A Molecular Cloning Manual (2003), Cold Spring Harbor Laboratory Press 523-525
29. Rosa G.J.M., et al. Reassessing design and analysis of two-colour microarray experiments using mixed effects models. Comp. Funct. Genomics 6 (2005) 123-131
30. Khanin R., and Wit E. Design of large time-course microarray experiments with two channels. Appl. Bioinformatics 4 (2005) 253-261
31. Naidoo S., et al. Microarray experiments: considerations for experimental design. S. Afr. J. Sci. 101 (2005) 347-354
32. Simon R.M., and Dobbin K. Experimental design of DNA microarray experiments. Biotechniques 34 (2003) 516-521
33. Vinciotti V., et al. An experimental evaluation of a loop versus a reference design for two-channel microarrays. Bioinformatics 21 (2005) 492-501
34. Routley B., and Muldoon M.R. Review: Practical design and analysis of 2-colour cDNA microarray experiments. MIMS Eprints (2007). http://www.eprints.ma.man.ac.uk/
35. Sterrenburg E., et al. A common reference for cDNA microarray hybridizations. Nucleic Acids Res. 30 (2002) e116
36. Williams B.A., et al. Genomic DNA as a cohybridization standard for mammalian microarray measurements. Nucleic Acids Res. 32 (2004) e81
37. Jin W., et al. The contribution of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat. Genet. 29 (2001) 389-395
38. Banerjee T., and Mukerjee R. Optimal factorial designs for cDNA microarray experiments. Ann. Appl. Stat. 2 (2007) 366-385
39. Hessner M.J., et al. Three color cDNA microarrays: quantitative assessment through the use of fluorescein-labeled probes. Nucleic Acids Res. 31 (2003) e14
40. Hessner M.J., et al. Use of three-color cDNA microarray platform to measure and control support-bound probe for improved data quality and reproducibility. Nucleic Acids Res. 31 (2003) e60
41. Alban A., et al. A novel experimental design for comparative two-dimensional gel analysis: two-dimensional difference gel electrophoresis incorporating a pooled internal standard. Proteomics 3 (2003) 36-44
42. Marouga R., et al. The development of the DIGE system: 2D fluorescence difference gel analysis technology. Anal. Bioanal. Chem. 382 (2005) 669-678
43. Woo Y., et al. Experimental design for three-color and four-color gene expression microarrays. Bioinformatics 21 (2005) i459-i467
44. Martin-Magniette M.L., et al. Normalization for triple-target microarray experiments. BMC Bioinformatics (2008) 9. http://www.biomedcentral.com 10.1186/1471-2105-9-216
45. Shaffer A.L., et al. IRF4 addiction in multiple myeloma. Nature 454 (2008) 226-231
46. Underhill-Day N., and Heath J.K. Oncostatin M (OSM) cytostasis of breast tumor cells: characterization of an OSM receptor B-specific kernel. Cancer Res. 66 (2006) 10891-10901
47. Bredel M., et al. Tumor necrosis factor-α-induced protein 3 as a putative regulator of nuclear-κB-mediated resistance to O6-alkylating agents in human glioblastomas. Am. J. Clin. Oncol. 24 (2006) 274-287
48. Critchley-Thorne R.J., et al. Down-regulation of the interferon signaling pathway in T lymphocytes from patients with metastatic melanoma. PLoS Med. 4 (2007) 897-911
49. de la Vega E., et al. Stress-induced gene expression profiling in the black tiger shrimp Penaeus monodon. Physiol. Genomics 31 (2007) 126-138
50. Maron L.G., et al. Transcriptional profiling of aluminum toxicity and tolerance responses in maize roots. New Phytol. 179 (2008) 116-128
51. Chang H.H., et al. Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 453 (2008) 544-547
52. Mager E.M., et al. Toxicogenomics of water chemistry influence on chronic lead exposure to the fathead minnow (Pimephales promelas). Aquat. Toxicol. 87 (2008) 200-209
53. Blangiardo M., et al. Using a calibration experiment to assess gene-specific information: full Bayesian and empirical Bayesian models for two-channel microarray data. Bioinformatics 22 (2006) 50-57
54. 't Hoen P.A.C., et al. Intensity-based analysis of two-colour microarrays enables efficient and flexible hybridization designs. Nucleic Acids Res. 32 (2004) e41
55. Fang H., et al. Self-self hybridization as an alternative experiment design to dye swap for two-color microarrays. OMICS 11 (2007) 14-24
56. Kelley R., et al. Correcting for gene-specific dye bias in DNA microarrays using the method of maximum likelihood. Bioinformatics 24 (2008) 71-77
57. Jaluria P., et al. A perspective on microarrays: current applications, pitfalls, and potential uses. Microb. Cell Fact. (2007) 6. http://www.microbialcellfactories.com 10.1186/1475-2859-6-4
58. Xiang Z., et al. Microarray expression profiling: analysis and applications. Curr. Opin. Drug Discov. Dev. 6 (2003) 384-395
59. Kendziorski C.M., et al. The efficiency of pooling mRNA in microarray experiments. Biostatistics 4 (2003) 465-477
60. Shih J.H., et al. Effects of pooling mRNA in microarray class comparisons. Bioinformatics 20 (2004) 3318-3325
61. Dobbin K., and Simon R. Sample size determination in microarray experiments for class comparison and prognostic classification. Biostatistics 6 (2005) 27-38
62. Draghici S., et al. Reliability and reproducibility issues in DNA microarray measurements. Trends Genet. 22 (2006) 101-109
63. Bylesjö M., et al. MASQOT: a method for cDNA microarray spot quality control. BMC Bioinformatics (2005) 6. http://www.biomedcentral.com 10.1186/1471-2105-6-250
64. Kim H.Y., et al. Characterization and simulation of cDNA microarray spots using a novel mathematical model. BMC Bioinformatics (2007) 8. http://www.biomedcentral.com 10.1186/1471-2105-8-485
65. King H.C., and Sinha A.A. Gene expression profile analysis by DNA microarrays: promise and pitfalls. J. Am. Med. Assoc. J. Am. Med. Assoc. 286 (2002) 2280-2288
66. Branham W.S., et al. Elimination of laboratory ozone leads to a dramatic improvement in the reproducibility of microarray gene expression measurements. BMC Biotechnol (2007). http://www.biomedcentral.com 10.1186/1472-6750-7-8
67. Fare T.L., et al. Effects of atmospheric ozone on microarray data quality. Anal. Chem. 75 (2003) 4672-4675
68. Dar M., et al. Development of a novel ozone- and photo-stable HyPer5 red fluorescent dye for array CGH and microarray gene expression analysis with consistent performance irrespective of environmental conditions. BMC Biotechnol. 8 (2008) 86
69. Patterson T.A., et al. Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project. Nat. Biotechnol. 24 (2006) 1140-1150
70. Peixoto B.R., et al. Evaluation of reference-based two-color methods for measurement of gene expression ratios using spotted cDNA microarrays. BMC Genomics (2006) 7. http://www.biomedcentral.com 10.1186/1471-2164-7-35