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Volumn 12, Issue , 2011, Pages

The projection score - an evaluation criterion for variable subset selection in PCA visualization

Author keywords

[No Author keywords available]

Indexed keywords

EVALUATION CRITERIA; EXPLORATORY ANALYSIS; HIGH DIMENSIONAL DATA; MICROARRAY DATA SETS; OBJECTIVE METHODS; SYNTHETIC DATASETS; VARIABLE SUBSET SELECTIONS; VISUALIZATION METHOD;

EID: 79960655875     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-12-307     Document Type: Article
Times cited : (37)

References (39)
  • 1
    • 0000325341 scopus 로고
    • On lines and planes of closest fit to systems of points in space
    • Pearson K. On lines and planes of closest fit to systems of points in space. Phil Mag (6) 1901, 2:559-572.
    • (1901) Phil Mag (6) , vol.2 , pp. 559-572
    • Pearson, K.1
  • 2
    • 58149421595 scopus 로고
    • Analysis of a complex of statistical variables into principal components
    • Hotelling H. Analysis of a complex of statistical variables into principal components. J Educ Psychol 1933, 24:417-441.
    • (1933) J Educ Psychol , vol.24 , pp. 417-441
    • Hotelling, H.1
  • 3
    • 0001710505 scopus 로고
    • Analysis of a complex of statistical variables into principal components (continued from September issue)
    • Hotelling H. Analysis of a complex of statistical variables into principal components (continued from September issue). J Educ Psychol 1933, 24:498-520.
    • (1933) J Educ Psychol , vol.24 , pp. 498-520
    • Hotelling, H.1
  • 6
    • 5444276626 scopus 로고    scopus 로고
    • Microarray gene expression profiling of B-cell chronic lymphocytic leukemia subgroups defined by genomic aberrations and VH mutation status
    • 10.1200/JCO.2004.12.133, 15459216
    • Haslinger C, Schweifer N, Stilgenbauer S, Döhner H, Lichter P, Kraut N, Stratowa C, Abseher R. Microarray gene expression profiling of B-cell chronic lymphocytic leukemia subgroups defined by genomic aberrations and VH mutation status. J Clin Oncol 2004, 22:3937-3949. 10.1200/JCO.2004.12.133, 15459216.
    • (2004) J Clin Oncol , vol.22 , pp. 3937-3949
    • Haslinger, C.1    Schweifer, N.2    Stilgenbauer, S.3    Döhner, H.4    Lichter, P.5    Kraut, N.6    Stratowa, C.7    Abseher, R.8
  • 7
    • 33750062866 scopus 로고    scopus 로고
    • Translating microarray data for diagnostic testing in childhood leukaemia
    • 10.1186/1471-2407-6-229, 1609180, 17002788
    • Hoffmann K, Firth MJ, Beesley AH, de Klerk NH, Kees UR. Translating microarray data for diagnostic testing in childhood leukaemia. BMC Cancer 2006, 6:229. 10.1186/1471-2407-6-229, 1609180, 17002788.
    • (2006) BMC Cancer , vol.6 , pp. 229
    • Hoffmann, K.1    Firth, M.J.2    Beesley, A.H.3    de Klerk, N.H.4    Kees, U.R.5
  • 8
    • 36749052234 scopus 로고    scopus 로고
    • Individual matrix metalloproteinases control distinct transcriptional responses in airway epithelial cells infected with Pseudomonas aeruginosa
    • 10.1128/IAI.00799-07, 2168342, 17923522
    • Kassim SY, Gharib SA, Mecham BH, Birkland TP, Parks WC, McGuire JK. Individual matrix metalloproteinases control distinct transcriptional responses in airway epithelial cells infected with Pseudomonas aeruginosa. Infect Immun 2007, 75:5640-5650. 10.1128/IAI.00799-07, 2168342, 17923522.
    • (2007) Infect Immun , vol.75 , pp. 5640-5650
    • Kassim, S.Y.1    Gharib, S.A.2    Mecham, B.H.3    Birkland, T.P.4    Parks, W.C.5    McGuire, J.K.6
  • 9
    • 5144229762 scopus 로고    scopus 로고
    • Immediate gene expression changes after the first course of neoadjuvant chemotherapy in patients with primary breast cancer disease
    • 10.1158/1078-0432.CCR-04-1031, 15475428
    • Modlich O, Prisack HB, Munnes M, Audretsch W, Bojar H. Immediate gene expression changes after the first course of neoadjuvant chemotherapy in patients with primary breast cancer disease. Clin Cancer Res 2004, 10:6418-6431. 10.1158/1078-0432.CCR-04-1031, 15475428.
    • (2004) Clin Cancer Res , vol.10 , pp. 6418-6431
    • Modlich, O.1    Prisack, H.B.2    Munnes, M.3    Audretsch, W.4    Bojar, H.5
  • 11
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Guyon I, Elisseeff A. An introduction to variable and feature selection. J Mach Learn Res 2003, 3:1157-1182.
    • (2003) J Mach Learn Res , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 12
    • 20444465712 scopus 로고    scopus 로고
    • Bayesian variable se-lection in clustering high-dimensional data
    • Tadesse MG, Sha N, Vannucci M. Bayesian variable se-lection in clustering high-dimensional data. J Am Stat Assoc 2005, 100(470):602-617.
    • (2005) J Am Stat Assoc , vol.100 , Issue.470 , pp. 602-617
    • Tadesse, M.G.1    Sha, N.2    Vannucci, M.3
  • 13
    • 33645505223 scopus 로고    scopus 로고
    • Variable selection for model-based clustering
    • Raftery AE, Dean N. Variable selection for model-based clustering. J Am Stat Assoc 2006, 101(473):168-178.
    • (2006) J Am Stat Assoc , vol.101 , Issue.473 , pp. 168-178
    • Raftery, A.E.1    Dean, N.2
  • 14
    • 0000146283 scopus 로고
    • Discarding variables in a principal component analysis. I: Artificial data
    • Jolliffe IT. Discarding variables in a principal component analysis. I: Artificial data. Appl Stat 1972, 21(2):160-173.
    • (1972) Appl Stat , vol.21 , Issue.2 , pp. 160-173
    • Jolliffe, I.T.1
  • 15
    • 0002008085 scopus 로고
    • Discarding variables in a principal component analysis. II: Real data
    • Jolliffe IT. Discarding variables in a principal component analysis. II: Real data. Appl Stat 1973, 22:21-31.
    • (1973) Appl Stat , vol.22 , pp. 21-31
    • Jolliffe, I.T.1
  • 16
    • 0021427712 scopus 로고
    • Principal variables
    • McCabe GP. Principal variables. Technometrics 1984, 26:127-134.
    • (1984) Technometrics , vol.26 , pp. 127-134
    • McCabe, G.P.1
  • 17
    • 84888275639 scopus 로고
    • Selection of variables to preserve multivariate data structure, using principal component analysis
    • Krzanowski WJ. Selection of variables to preserve multivariate data structure, using principal component analysis. Appl Stat 1987, 6:51-56.
    • (1987) Appl Stat , vol.6 , pp. 51-56
    • Krzanowski, W.J.1
  • 21
    • 43049086717 scopus 로고    scopus 로고
    • Sparse principal component analysis via regularized low rank matrix approximation
    • Shen H, Huang JZ. Sparse principal component analysis via regularized low rank matrix approximation. J Multivar Anal 2008, 99:1015-1034.
    • (2008) J Multivar Anal , vol.99 , pp. 1015-1034
    • Shen, H.1    Huang, J.Z.2
  • 22
    • 70149096300 scopus 로고    scopus 로고
    • A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
    • 10.1093/biostatistics/kxp008, 2697346, 19377034
    • Witten DM, Tibshirani R, Hastie T. A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 2009, 10:515-534. 10.1093/biostatistics/kxp008, 2697346, 19377034.
    • (2009) Biostatistics , vol.10 , pp. 515-534
    • Witten, D.M.1    Tibshirani, R.2    Hastie, T.3
  • 23
    • 85194972808 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc Series B 1996, 58:267-288.
    • (1996) J R Stat Soc Series B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 24
    • 16244401458 scopus 로고    scopus 로고
    • Regularization and variable selection via the elastic net
    • Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Series B 2005, 67:301-320.
    • (2005) J R Stat Soc Series B , vol.67 , pp. 301-320
    • Zou, H.1    Hastie, T.2
  • 28
    • 77957575067 scopus 로고    scopus 로고
    • Finding large average submatrices in high dimensional data
    • Shabalin AA, Weigman VJ, Perou CM, Nobel AB. Finding large average submatrices in high dimensional data. Ann Appl Stat 2009, 3(3):985-1012.
    • (2009) Ann Appl Stat , vol.3 , Issue.3 , pp. 985-1012
    • Shabalin, A.A.1    Weigman, V.J.2    Perou, C.M.3    Nobel, A.B.4
  • 29
    • 33747883187 scopus 로고    scopus 로고
    • Novel unsupervised feature filtering of biological data
    • 10.1093/bioinformatics/btl214, 16873514
    • Varshavsky R, Gottlieb A, Linial M, Horn D. Novel unsupervised feature filtering of biological data. Bioinformatics 2006, 22:e507-513. 10.1093/bioinformatics/btl214, 16873514.
    • (2006) Bioinformatics , vol.22
    • Varshavsky, R.1    Gottlieb, A.2    Linial, M.3    Horn, D.4
  • 31
    • 19044395321 scopus 로고    scopus 로고
    • How many principal components? stopping rules for determining the number of non-trivial axes revisited
    • Peres-Neto PR, Jackson DA, Somers KM. How many principal components? stopping rules for determining the number of non-trivial axes revisited. Comput Stat Data Anal 2005, 49:974-997.
    • (2005) Comput Stat Data Anal , vol.49 , pp. 974-997
    • Peres-Neto, P.R.1    Jackson, D.A.2    Somers, K.M.3
  • 32
    • 54949118365 scopus 로고    scopus 로고
    • Statistical significance of clustering for high dimension low sample size data
    • Liu Y, Hayes DN, Nobel A, Marron JS. Statistical significance of clustering for high dimension low sample size data. J Am Stat Assoc 2008, 103:1281-1293.
    • (2008) J Am Stat Assoc , vol.103 , pp. 1281-1293
    • Liu, Y.1    Hayes, D.N.2    Nobel, A.3    Marron, J.S.4
  • 35
    • 33749550338 scopus 로고    scopus 로고
    • Prediction by supervised principal components
    • Tech. rep., Stanford University
    • Bair E, Hastie T, Paul D, Tibshirani R. Prediction by supervised principal components. 2004, Tech. rep., Stanford University.
    • (2004)
    • Bair, E.1    Hastie, T.2    Paul, D.3    Tibshirani, R.4
  • 36
    • 0347989448 scopus 로고    scopus 로고
    • Methodologies in spectral analysis of large dimensional random matrices, a review
    • Bai ZD. Methodologies in spectral analysis of large dimensional random matrices, a review. Stat Sin 1999, 9:611-677.
    • (1999) Stat Sin , vol.9 , pp. 611-677
    • Bai, Z.D.1
  • 37
    • 0035641726 scopus 로고    scopus 로고
    • On the distribution of the largest eigenvalue in principal components analysis
    • Johnstone IM. On the distribution of the largest eigenvalue in principal components analysis. Ann Stat 2001, 29:295-327.
    • (2001) Ann Stat , vol.29 , pp. 295-327
    • Johnstone, I.M.1
  • 39
    • 35948933029 scopus 로고    scopus 로고
    • On the number of principal components: A test of dimensionality based on measurements of similarity between matrices
    • Dray S. On the number of principal components: A test of dimensionality based on measurements of similarity between matrices. Comput Stat Data Anal 2008, 52:2228-2237.
    • (2008) Comput Stat Data Anal , vol.52 , pp. 2228-2237
    • Dray, S.1


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