Associating phenotypes with molecular events: Recent statistical advances and challenges underpinning microarray experiments

Functional and Integrative Genomics

Volumn 6, Issue 1, 2006, Pages 1-13

  Liang, Yulan ^a   Kelemen, Arpad ^b  

^a UNIVERSITY AT BUFFALO   (United States)

^b NIAGARA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYES THEOREM; BIOLOGICAL MODEL; CORRELATION ANALYSIS; DNA MICROARRAY; ENVIRONMENTAL FACTOR; GENE EXPRESSION; GENE FUNCTION; GENE MAPPING; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENETIC DISORDER; GENETIC SCREENING; GENOME; GENOTYPE; MOLECULAR BIOLOGY; PHENOTYPE; PREDICTION; PRIORITY JOURNAL; QUALITY CONTROL; QUANTITATIVE TRAIT; REAL TIME POLYMERASE CHAIN REACTION; RELIABILITY; REPRODUCIBILITY; REVIEW; STATISTICAL ANALYSIS;

ALGORITHMS; BIOLOGICAL MARKERS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PHENOTYPE; SOFTWARE;

EID: 29544434311     PISSN: 1438793X     EISSN: 14387948     Source Type: Journal    
DOI: 10.1007/s10142-005-0006-z     Document Type: Review

References (114)

1. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Automat Contr 19:716-723 10.1109/TAC.1974.1100705
2. Alter O, Brown PO, Botstein D (2000) Singular value decomposition for genome-wide expression data processing and modeling. Proc Natl Acad Sci U S A 97:10101-10106 10.1073/pnas.97.18.10101
3. Bailar JC (1997) The promise and problems of meta-analysis (editorial). N Engl J Med 337:559-561 10.1056/NEJM199708213370810
4. Baldi P, Long AD (2001) A Bayesian framework for the analysis of microarray expression data: Regularized t-test and statistical inferences of gene changes. Bioinformatics 17(6):509-519 10.1093/ bioinformatics/17.6.509
5. Ball RD (2001) Bayesian methods for quantitative trait loci mapping based on model selection: Approximate analysis using the Bayesian information criterion. Genetics 159:1351-1364 11729175
6. Barczak A, Rodriguez MW, Hanspers K, Koth LL, Tai YC, Bolstad BM, Speed TP, Erle DJ (2003) Spotted long oligonucleotide arrays for human gene expression analysis. Genome Res 13:1775-1785 10.1101/gr.1048803
7. Beal MJ, Falciani FL, Ghahramani Z, Rangel C, Wild D (2005) A Bayesian approach to reconstructing genetic regulatory networks with hidden factors. Bioinformatics 21:349-356 10.1093/bioinformatics/bti014
8. Beaumont MA, Rannala B (2004) The Bayesian revolution in genetics. Nat Rev Genet 5:251-261 10.1038/nrg1318
9. Beissbarth T, Speed TP (2004) GOstat: Find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics 20(9):1464-1465 10.1093/bioinformatics/bth088
10. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc B 57:289-300
11. Black MA, Doerge RW (2002) Calculation of the minimum number of replicate spots required for detection of significant gene expression fold change in microarray experiments. Bioinformatics 18(12):1609-1616 10.1093/bioinformatics/18.12.1609
12. Botstein D, Risch N (2003) Discovering genotypes underlying human phenotypes: Past successes for mendelian disease, future approaches for complex disease. Nat Genet 33(Suppl):228-237 10.1038/ng1090
13. Breslin T, Eden P, Krogh M (2004) Comparing functional annotation analyses with Catmap. BMC Bioinformatics 5:193 10.1186/1471-2105-5-193
14. Broet P, Richardson S, Radvanyi F (2002) Bayesian hierarchical model for identifying changes in gene expression from microarray experiments. J Comput Biol 9(4):671-683 10.1089/106652702760277381
15. Broman KW, Speed TP (2002) A model selection approach for the identification of quantitative trait loci in experimental crosses (with discussion). J R Stat Soc B 64:641-656 (731-775) 10.1111/1467-9868.00354
16. Brown MP, Grundy WN, Lin D, Cristianini N, Sugnet CW, Furey TS, Junior MA, Haussler D (2000) Knowledge-based analysis of microarray gene expression data by using supported vector machines. Proc Natl Acad Sci U S A 97(1):262-267 10.1073/pnas.97.1.262
17. Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963-971 7851788
18. Cui X, Churchill G (2003) Statistical tests for differential expression in cDNA microarray experiments. Genome Biol 4:210 10.1186/gb-2003-4-4-210
19. Darvasi A (2003) Genomics - gene expression meets genetics. Nature 422:269-270 10.1038/422269a
20. Datta S, Datta S et al (2003) Comparisons and validation of statistical clustering techniques for microarray gene expression data. Bioinformatics 19:459-466 10.1093/bioinformatics/btg025
21. Do K, Muller P, Tang F (2005) A Bayesian mixture model for differential gene expression. J R Stat Soc C 54(3):627-644 10.1111/ j.1467-9876.2005.05593.x
22. Doerge RW (2002) Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet 3:43-52 11823790
23. Doerge RW, Churchill GA (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics 142:285-294 8770605
24. Doerge RW, Zeng ZB, Weir BS (1997) Statistical issues in the search for genes affecting quantitative traits in experimental populations. Stat Sci 12:195-219 10.1214/ss/1030037909
25. Dudoit S, Fridlyand J (2002) A prediction-based resampling method to estimate the number of clusters in a dataset. Genome Biol 3:RESEARCH0036 10.1186/gb-2002-3-7-research0036
26. Dudoit S, Fridlyand J, Speed T (2002a) Comparison of discrimination methods for the classification of tumors using gene expression data. J Am Stat Assoc 97(457):77-87 10.1198/016214502753479248
27. Dudoit S, Yang YH, Speed TP, Callow MJ (2002b) Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Stat Sin 12:111-139
28. Durbin BP, Hardin JS, Hawkins DM, Rocke DM (2002) A variance-stabilizing transformation for gene-expression microarray data. Bioinformatics 18:105-110
29. Dysvik THB et al (2004) LSimpute: Accurate estimation of missing values in microarray data with least squares methods. Nucleic Acids Res 32(3)
30. Edwards J, Page GP, Gadbury G, Heo M, Kayo T, Weindruch R, Allison D (2005) Empirical Bayes estimation of gene specific effects in microarray research. Funct Integr Genomics 5:32-39 10.1007/s10142-004-0123-0
31. Efron B (1996) Empirical Bayes methods for combining likelihoods (with discussion). J Am Stat Assoc 91:538-565
32. Efron B, Morris C (1975) Data analysis using Stein's estimator and its generalization. J Am Stat Assoc 70(350):311-319
33. Efron B, Tibshirani R, Goss V, Chu G (2001) Empirical Bayes analysis of a microarray experiment. J Am Stat Assoc 96(456):1151-1160 10.1198/ 016214501753382129
34. Ehm MG, Kimmel M, Cottingham RW (1996) Error detection for genetic data, using likelihood methods. Am J Hum Genet 58:225-234 8554060
35. Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 95:14863-14868 10.1073/pnas.95.25.14863
36. Gasch AP, Eisen MB (2002) Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering. Genome Biol 3(11)
37. Ghosh D (2005) Nonparametric methods for analyzing replication origins in genomewide data. Funct Integr Genomics 5:18-27 (5:28-31) 10.1007/ s10142-004-0120-3
38. Ghosh D, Chonnaiyan A (2003a) Covariate adjustment in the analysis of microarray data from clinical studies. Funct Integr Genomics 5:18-27 10.1007/s10142-004-0120-3
39. Ghosh D, Barette T, Rhodes D (2003b) Statistical issues and methods for meta-analysis of microarray data: A case study in prostate cancer. Funct Integr Genomics 3:180-188 10.1007/s10142-003-0087-5
40. Glynn D, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA (2003) DAVID: Database for annotation, visualization, and integrated discovery. Genome Biol 4:R60 10.1186/gb-2003-4-9-r60
41. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caliguiri MA, Bloomfield CD, Lander ES (1999) Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 286:531-537
42. Hastiel T, Tibshirani R, Eisen MB, Alizadeh A, Levy R, Staudt L, Chan WC, Botstein D, Brown PO (2000) Gene shaving as a method for identifying distinct sets of genes with similar expression patterns. Genome Biol 1(2):rEsearch0003.1-research0003.21 10.1186/gb-2000-1-2-research0003
43. Hoeting J, Madigan D, Raftery A, Volinsky C (1999) Bayesian model averaging: A tutorial. Stat Sci 14(4):382-417 10.1214/ss/1009212519
44. Hosack D, Hosack A, Sherman BT, Lane HC, Lempicki RA (2003) Identifying biological themes within lists of genes with EASE. Genome Biol 4:R70 10.1186/gb-2003-4-10-r70
45. Ibrahim JG, Chen M-H, Gray RJ (2002) Bayesian models for gene expression with DNA microarray data. J Am Stat Assoc 3:88-99 10.1198/ 016214502753479257
46. Ibrahim AFM, Hedley PE, Cardle L, Kruger W, Marshall DF, Muehlbauer GJ, Waugh R (2005) A comparative analysis of transcript abundance using SAGE and Affymetrix arrays. Funct Integr Genomics 5:163-174 10.1007/ s10142-005-0135-4
47. Irizarry RA, Bolstad BM, Collin F, Cope L, Hobbs B, Speed T (2003) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 31(4):e15 10.1093/nar/gng015
48. Irizarry RA et al (2005) Multiple-laboratory comparison of microarray platforms. Nat Methods 2:345-349 10.1038/nmeth756
49. IT Jolliffe 1986 Principal component analysis Springer Berlin Heidelberg New York
50. Jolliffe IT, Uddin M (2003) A modified principal component technique base on the lasso. J Comput Graph Stat 12:531-547 10.1198/1061860032148
51. Keller AD, Schummer M, Hood L, Ruzzo WL (2000) Bayesian classification of DNA array expression data. Technical Report UW-CSE-2000-08-01
52. Kerr M, Churchill (2000) Analysis of variance for gene expression microarray data. J Comput Biol 7:819-837 10.1089/10665270050514954
53. Kerr M, Churchill G (2001) Bootstrapping cluster analysis: Assessing the reliability of conclusions from microarray experiments. Proc Natl Acad Sci U S A 97:8961-8965 10.1073/pnas.161273698
54. Khan J, Wei JS, Ringner M, Saal LH, Ladanyi M, Westermann F, Berthold F, Schwab M, Antonescu CR, Peterson C, Meltzer PS (2001) Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med 7(6):673-679 10.1038/89044
55. Larkin JE et al (2005) Independence and reproducibility across microarray platforms. Nat Methods 2:337-343 10.1038/nmeth757
56. Lee ML, Whitmore GA (2002) Power and sample size for DNA microarray studies. Stat Med 21:3543-3570 10.1002/sim.1335
57. Lee MT, Kuo FC, Whitmore GA, Sklar J (2000) Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations. Proc Natl Acad Sci U S A 97(18):9834-9839 10.1073/pnas.97.18.9834
58. Lee HK, Hsu AK, Sajdak J, Qin J, Pavlidis P (2004) Coexpression analysis of human genes across many microarray data sets. Genome Res 14:1085-1094 10.1101/gr.1910904
59. Li C, Wong WH (2001) Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc Natl Acad Sci U S A 98(1):31-36 10.1073/pnas.011404098
60. Li Y, Campbell C, Tipping M (2002) Bayesian automatic relevance determination algorithms for classifying gene expression data. Bioinformatics 18:1332-1339 10.1093/bioinformatics/18.10.1332
61. Liang Y, Kelemen A (2004) Hierarchical Bayesian neural network for gene expression temporal patterns. J Stat Appl Genet Mol Biol 3(1) Article 20
62. Liang Y, Tayo B, Cai X, Kelemen A (2005) Differential and trajectory methods for time course gene expression data. Bioinformatics 20(13):3009-3016 10.1093/bioinformatics/bti465
63. B Liu 1998 Statistical genomics: Linkage, mapping and QTL analysis CRC Boca Raton
64. Lonnstedt I, Speed T (2002) Replicated microarray data. Stat Sin 12(1):31-46
65. Luan Y, Li H (2004) Model-based methods for identifying periodically regulated genes based on the time course microarray gene expression data. Bioinformatics 20:332-339 (01) 10.1093/bioinformatics/btg413
66. MacKay DJC (1995) Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks. Network: Comput Neural Syst 6(3):469-505 10.1088/0954-898X/6/3/011
67. McShane LM, Radmacher MD, Friedlin B, Yu R, Li MC, Simon R (2002) Methods for assessing reproducibility of clustering patterns observed in analyses of microarray data. Bioinformatics 18:1462-1469 10.1093/ bioinformatics/18.11.1462
68. AC Merlise 1998 Bayesian model averaging and model search strategies In: JM Bernardo JO Berger AP Dawid AFM Smith (eds) Bayesian statistics 6 Oxford University Press Oxford
69. Members of the Toxicogenomics Research Consortium (2005) Standardizing global gene expression analysis between laboratories and across platforms. Nat Methods 2:351-356
70. Monti S, Tamayo P, Mesirov JP, Golub TR (2003) Consensus clustering: A resampling-based method for class discovery and visualization of gene expression microarray data. Mach Learn 2003 52(1-2):91-118 10.1023/ A:1023949509487
71. Morris CN (1983) Parametric empirical Bayes inference: Theory and applications. J Am Stat Assoc 78:47-65
72. Neal SH, Madhusmita M, Holter NS, Mitra M, Maritan A, Cieplak M, Banavar JR, Fedoroff VF (2000) Fundamental patterns underlying gene expression profiles: Simplicity from complexicity. Proc Natl Acad Sci U S A 97:8409-8414 10.1073/pnas.150242097
73. Nettleton D, Doerge RW (2000) Accounting for variability in the use of permutation testing to detect quantitative trait loci. Biometrics 56:52-58 10.1111/j.0006-341X.2000.00052.x
74. Newton MA, Kendziorski CM, Richmond CS, Blattner FR, Tsui KW (2001) On differential variability of expression ratios, improving statistical inference about gene expression changes from microarray data. J Comput Biol 8:37-52 10.1089/106652701300099074
75. Nimgaonkar A, Sanoudou D, Butte AJ, Haslett JN, Kunkel LM, Beggs AH, Kohane IS (2003) Reproducibility of gene expression across generations of Affymetrix microarrays. BMC Bioinformatics 4(1):27 10.1186/ 1471-2105-4-27
76. Ooi CH, Tan P (2003) Genetic algorithms applied to multi-class prediction for the analysis of gene expression data. Bioinformatics 19(1):37-44 10.1093/bioinformatics/19.1.37
77. Pan W (2002) A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments. Bioinformatics 18(4):546-549 10.1093/bioinformatics/18.4.546
78. Pan W, Lin J, Le CT (2002) How many replicates of arrays are required to detect gene expression changes in microarray experiments? A mixture model approach. Genome Biol 3(5):REsearch0022
79. Parmigiani G, Garrett-Mayer ES, Anbazhagan R, Gabrielson E (2004) A cross-study comparison of gene expression studies for the molecular classification of lung cancer. Clin Cancer Res 10:2922-2927 10.1158/ 1078-0432.CCR-03-0490
80. Pochet N, Smet F, Suykens J, De Moor J (2004) Systematic benchmarking of microarray data classification: Assessing the role of non-linearity and dimensionality reduction. Bioinformatics 20:3185-3195 10.1093/ bioinformatics/bth383
81. Ramoni MF, Sebastiani P, Kohane IS (2002) Cluster analysis of gene expression dynamics. Proc Natl Acad Sci U S A 99(14):9121-9126 10.1073/ pnas.132656399
82. Rhodes D, Yu J, Shanker K et al (2004) Large scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. Proc Natl Acad Sci U S A 101(25):9309-9314 10.1073/pnas.0401994101
83. H Robbins 1955 An empirical Bayes approach to statistics Proceedings of the 3rd Berkeley symposium on mathematical statistics and probability, 1 University of California Press Berkeley, CA 157-164
84. Romualdi C, Campanaro S, Campagna D, Celegato B, Cannata N, Toppo S, Valle G, Lanfranchi G (2003) Pattern recognition in gene expression profiling using DNA array: A comparative study of different statistical methods applied to cancer classification. Hum Mol Genet 12(8):823-836 10.1093/hmg/ddg093
85. P Sham 2001 Statistics in human genetics Oxford University Press Oxford
86. Sillanpaa MJ, Arjas E (2002) Model choice in gene mapping: What and why. Trends Genet 18:301-307 10.1016/S0168-9525(02)02688-4
87. Simon R, Radmacher MD, Dobbin K, McShane LM (2003) Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. J Natl Cancer Inst 95(1):14-18 12509396
88. Slonim DK (2002) From patterns to pathways: Gene expression data analysis comes of age. Nat Genet Suppl 32:502 10.1038/ng1033
89. Smyth GK (2004) Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3(1) Article 3
90. GK Smyth T Speed 2003 Normalization of cDNA microarray data D Carter Methods: Selecting candidate genes for DNA array screens. Application to neuroscience Elsevier Amsterdam 265-273
91. Smyth GK, Michaud J, Scott HS (2005) Use of within-array replicate spots for assessing differential expression in microarray experiments. Bioinformatics 21(9):2067-2075 10.1093/bioinformatics/bti270
92. Spiegelhalter et al (2002) Bayesian measures of model complexity and fit. J R Stat Soc B 583-639
93. Stone M (1974) Cross-validatory choice and assessment of statistical predictions (with discussion). J R Stat Soc B 36:111-147
94. Storey JD (2003) The positive false discovery rate: A Bayesian interpretation and the q-value. Ann Stat 31(6):2013-2035 10.1214/aos/ 1074290335
95. Szabo A, Boucher K, Carrol WL, Klebanov LB, Tsodikov AD, Yakovlev AY (2002) Variable selection and pattern recognition with gene expression data generated by the microarray technology. Math Biosci 176:71-98 10.1016/S0025-5564(01)00103-1
96. Tamayo T, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander ES, Golub TR (1999) Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proc Natl Acad Sci U S A 96:2907-2912 10.1073/ pnas.96.6.2907
97. Tan PK, Downey TJ, Spitznagel EL Jr, Xu P, Fu D, Dimitrov DS, Lempicki RA, Raaka BM, Cam MC (2003) Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res 31(19)
98. Troyanskaya OG, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB (2001) Missing value estimation methods for DNA microarrays. Bioinformatics 17:520-525 10.1093/bioinformatics/17.6.520
99. Troyanskaya OG, Garber ME, Brown P, Botstein D, Altman RB (2002) Nonparametric methods for identifying differentially expressed genes in microarray data. Bioinformatics 18(11):1454-1461 10.1093/bioinformatics/ 18.11.1454
100. Troyanskaya OG, Dolinski K, Owen AO, Altman RB, Botstein D (2003) A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae). Proc Natl Acad Sci U S A 100:8348-8353 10.1073/pnas.0832373100
101. Tseng GC, Oh MK, Rohlin L, Liao JC, Wong WH (2001) Issues in cDNA microarray analysis: Quality filtering, channel normalization, models of variations and assessment of gene effects. Nucleic Acids Res 29(12):2549-2557 11410663
102. Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 9:5116-5121 10.1073/pnas.091062498
103. Visscher PM, Thompson R, Haley CS (1996) Confidence intervals in QTL mapping by bootstrapping. Genetics 143:1013-1020 8725246
104. Wall ME, Dyck PA, Brettin TS (2001) SVDMAN-Singular value decomposition analysis of microarray data. Bioinformatics 17:566-568 10.1093/ bioinformatics/17.6.566
105. B Weir 1996 Genetic data analysis II Sinauer Sunderland
106. West M (2000) Bayesian regression analysis in the "Large p, Small n" paradigm. Technical Report 00-22, Institute of Statistics and Decision Sciences, Duke University, CSE-2000-08-01
107. Wolfinger RD, Gibson G, Wolfinger ED, Bennett L, Hamadeh H, Bushel P, Afshari C, Paules R (2001) Assessing gene significance from cDNA microarray expression data via mixed models. J Comp Biol 8(6):625-637 10.1089/106652701753307520
108. Wuju L, Momiao X (2002) Tclass: Tumor classification system based on gene expression profile. Bioinformatics 18:325-326 10.1093/ bioinformatics/18.2.325
109. Xiao Y, Frisina R, Gordon A, Klebanov L, Yakovlev A (2004) Multivariate search for differentially expressed gene combinations. BMC Bioinformatics 5(1):164 10.1186/1471-2105-5-164
110. Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP (2002) Normalization for cDNA microarray data. Nucleic Acids Res 30(4):e15 10.1093/nar/30.4.e15
111. Yeung KY, Ruzzo WL (2001) Principal component analysis for clustering gene expression data. Bioinformatics 17(9):763-774 10.1093/ bioinformatics/17.9.763
112. Yeung et al (2003) Clustering gene-expression data with repeated measurements. Genome Biol 4:R34.1-R34.17
113. Zien A, Fluck J, Zimmer R, Lengauer T (2003) Microarrays: How many do you need? J Comput Biol 10(3-4):653-667 10.1089/10665270360688246
114. Zou H, Hastie T et al (2004) Sparse principal component analysis. J Comput Graph Stat (in press)