Statistical Methods for Gene Expression Data

  • Kim, Choongrak (Department of Statistics, Pusan National University)
  • Published : 2004.04.01


Since the introduction of DNA microarray, a revolutionary high through-put biological technology, a lot of papers have been published to deal with the analyses of the gene expression data from the microarray. In this paper we review most papers relevant to the cDNA microarray data, classify them in statistical methods' point of view, and present some statistical methods deserving consideration and future study.


  1. Nature v.403 Different types of diffuse large b-cell lymphoma identified by gene expression profiling Alizadeh,A.A.;Eisen,M.B.;Davis,R.E.;Ma,C.;Lossos,I.S.;Rosenwald,A.;Boldrick,J.C.;Sabet,H.;Tran,T.;Yu,X.;Powell,J.L.;Yang,L.;Marti,G.E.;Moore,T.;Hudson,Jr.J.;Lu,L.;Lewis,D.B.;Tibshirani,R.;Sherlock,G.;Chan,W.C.;Greiner,T.C.;Weisenburger,D.D.;Armitage,J.O.;Warnke,R.;Levy,R.;Levy,R.;Wilson,W.;Grever,M.R.;Byrd,J.C.;Brown,P.O.;Bostein,D.;Staudt,L.M.
  2. Proceedings of the National Academy of Science v.97 Singular value decomposition for genome-wide expression data prcessing and modeling Alter,O.;Brown,P.O.;Bostein,D.
  3. Nature Genetics v.21 Gene expression informatics - it's all in your mine Basset,D.E.;Eisen,M.B.;Boguski,M.S.
  4. Journal of Computational Biology v.7 Tissue classification with gene expression profiles Ben-Dor,A.;Bruhn,L.K.;Friedman,N.;Nachman,L.;Schummer,M.;Yakini,Z.
  5. Bioinformatics v.20 Adjustment of systematic microarray data biases Beito,M.;Parker,J.;u,Q.;쪄,J.;Xiang,D.;Perou,C.M.;Marron,J.S.
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  9. Federation of European Biochemical Societies Letters v.480 Gene expression data analysis Brazma,A.;Vilo,J.
  10. Machine Learning v.24 Bagging predictors Breiman,L.
  11. Classification and Regression Trees Breiman,L.;Friedman,J.H.;Olshen,R.;Stone,C.J.
  12. Proceedings of the National Academy of Science v.97 Knowledge-based analysis of microarray gene expression data by using support vector machines Brown,M.P.S;Grundy,W.N.;Lin,D.;Cristianini,N.;Sugnet,C.W.;Furey,T.S.;Ares,Jr.M.;Haussler,D.
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  22. Bioinformatics v.19 Bagging to improve the accuracy of a clustering procedure Dudoit,S.;Fridlyand,J.
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  30. Science v.286 Molecular classification of cancer:class discovery and class prediction by gene expression monitoring Golub,T.R.;Slonim,D.K.;Tamayo,P.;Huard,C.;Gaasenbeek,M.;Mesirov,J.P.;Coller,H.;Loh,M.L.;Downing,J.R.;Caligiuri,M.A.;Bloomfield,C.D.;Lander,E.S.
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  33. Proceedings of the National Academy of Science v.97 Fundamental patterns underlying gene expression profiles: Simplicity from complexity Holster,N.S.;Mitra,M.;Maritan,A.;Cieplak,M.;Banavar,J.R.
  34. Proceedings of the National Academy of Science v.98 Dynamic modeling of gene expression data Holster,N.S.;Martian,A.;Cieplak,M.;Fedroff,N.V.;Banavar,J.R.
  35. Journal of the American Statistical Association v.97 Bayesian models for gene expression with DNA microarray data Ibrahim,J.G.;Chen,M-H.;Gray,R.J.
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  41. Proceedings of the National Academy of Science v.97 Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations Lee,M.T.;Kuo,F.C.;Whitemore,G.A.;Sklar,J.
  42. Bioinformatics v.19 Classification of multiple cancer types by multicategory support vector machines using gene expression data Lee,Y.;Lee,C-K.
  43. Nature Genetics no.SUP.21 High-density synthetic oilgonucleotide arrays Lipshutz,R.J.;Fordor,S.;Gingeras,T.;Lockhart,D.
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  49. Proceedings of the National Academy of Science v.16 Distinctive gene expression patterns in human mammary epithelial cells and breast cancers Perou,C.M.;Jeffrey,S.S.;van de Rijn,M.;Rees,C.A.;Eisen,M.B.;Ross,D.T.;Pergamenschikov,A.;Williams,C.F.;Zhu,S.X.;Lee,J.C.;Lashkari,D.;Shalon,D.;Brown,P.O.;Botstein,D.
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  52. Pattern Recognition and Neural Networks Ripley,B.D.
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  54. Journal of Cellular Biochemistry v.80 Analyzing high-density oligonucleotide gene expression array data Schadt,E.E.;Li,C.;Su,C.;Wong,W.H.<192::AID-JCB50>3.0.CO;2-W
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  56. Science v.270 Quantitative monitoring of gene expression patterns with a complementary DNA microarray Schena,M.;Shalon,D.;Davis,R.W.;Brown,P.O.
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  60. Methods and Protocols,To appear Statistical issues in cDNA microarray data analysis,Functional Genomics Smyth,G.K.;Yang,Y.H.;Speed,T.
  61. Molecular Biology of the Cell v.9 Comprehensive identification of cell cycle-regulated genes of the yeast saccaromyces cerevisiae by microarray hybridization Spellman,P.T.;Sherlock,G.;Zhang,M.Q.;Iyer,V.R.;Andres,K.;Eisen,M.B.;Brown,P.O.;Bostein,D.;Futcher,B.
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  63. Proceedings of the National Academy of Science v.96 Interpreting patterns of gene expression with self-organizing mpas: Methods and applications to hematopoietic differentiation Tamayo,P.;Slonim,T.;Mesirov,J.;Zhu,Q.;Kitareewan,S.;Dmitrovsky,E.;Lander,E.S.;Golub,T.R.
  64. Technical Report,Department of Health Research and Policy Clustering methods for the analysis of dna microarray data Tibshirani,R.;Hastie,T.;Eisen,M.;Ross,D.T.;Botstein,D.;Brown,P.O.
  65. Proceedings of the National Academy of Science v.99 Diagnosis of multiple cancer types by shrunken centroids of gene expression Tibshirani,R.;Hastie,T.;Narasimhan,B.;Chu,G.
  66. Nucleic Acids Research v.29 Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects Tseng,G.C.;Oh,M-K;Rohlin,L.;Liao,J.C.;Wong,W.H.
  67. Proceedings of the National Academy of Science v.98 Significance analysis of microarrays applied to the ionizing radiation response Tusher,V.G.;Tibshirani,R.;Chu,G.
  68. Statistical Learning Theory Vapnik,V.N.
  69. Bioinformatics v.20 A generalized likelihood ratio test to identify differentially expressed genes from microarray data Wang,S.;Ethier,S.
  70. Resampling-based Multiple Testing: Examples and Methods for P-value Adjustment Westfall,P.H.;Young,S.S.
  71. Bioinformatics v.19 New normalization methods for cDNA microarray data Wilson,D.L.;Buckley,M.J.;Helliwell,C.A.;Wilson,I.W.
  72. Journal of Computational Biology v.8 Assessing gene significance from cDNA microarray expression data via mixed models Wolfinger,R.D.;Gibson,G.;Wolfinger,E.D.;Bennett,L.;Madadeh,H.;Bushel,P.;Afshari,C.;Paules,R.S.
  73. Journal of Computational and Graphical Statistics v.11 Comparison of methods for image analysis on cDNA microarray data Yang,Y.H.;Buckley,M.J.;Dudoit,S.;Speed,T.P.
  74. Proceedings of SPIE Normalization for cDNA microarray data in Microarrays: Optical Technologies and Informatics Yang,Y.H.;Dudoits,S.;Luu,P.;Speed,T.P.