Feature selection in omics prediction problems using cat scores and false nondiscovery rate control
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[1] E. B. Wilson,et al. The Distribution of Chi-Square. , 1931, Proceedings of the National Academy of Sciences of the United States of America.
[2] B. Efron. The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis , 1975 .
[3] J. Friedman. Regularized Discriminant Analysis , 1989 .
[4] J. Hintze,et al. Violin plots : A box plot-density trace synergism , 1998 .
[5] Ash A. Alizadeh,et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling , 2000, Nature.
[6] M. Ringnér,et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks , 2001, Nature Medicine.
[7] T. Poggio,et al. Prediction of central nervous system embryonal tumour outcome based on gene expression , 2002, Nature.
[8] E. Lander,et al. Gene expression correlates of clinical prostate cancer behavior. , 2002, Cancer cell.
[9] Geoffrey J McLachlan,et al. Selection bias in gene extraction on the basis of microarray gene-expression data , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[10] R. Tibshirani,et al. Diagnosis of multiple cancer types by shrunken centroids of gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[11] B. Efron. Large-Scale Simultaneous Hypothesis Testing , 2004 .
[12] Trevor Hastie,et al. Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays , 2003 .
[13] Trevor Hastie,et al. Regularized Discriminant Analysis and Its Application in Microarrays , 2004 .
[14] P. Bickel,et al. Some theory for Fisher''s linear discriminant function , 2004 .
[15] K. Strimmer,et al. Statistical Applications in Genetics and Molecular Biology A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics , 2011 .
[16] Songcan Chen,et al. Modified linear discriminant analysis , 2005, Pattern Recognit..
[17] David J. Hand,et al. Classifier Technology and the Illusion of Progress , 2006, math/0606441.
[18] Trevor Hastie,et al. Regularized linear discriminant analysis and its application in microarrays. , 2007, Biostatistics.
[19] Korbinian Strimmer,et al. Statistical Applications in Genetics and Molecular Biology , 2005 .
[20] John D. Storey,et al. Optimality Driven Nearest Centroid Classification from Genomic Data , 2007, PloS one.
[21] Korbinian Strimmer,et al. A unified approach to false discovery rate estimation , 2008, BMC Bioinformatics.
[22] Jianqing Fan,et al. High Dimensional Classification Using Features Annealed Independence Rules. , 2007, Annals of statistics.
[23] Korbinian Strimmer,et al. A general modular framework for gene set enrichment analysis , 2009, BMC Bioinformatics.
[24] M. Newton. Large-Scale Simultaneous Hypothesis Testing: The Choice of a Null Hypothesis , 2008 .
[25] D. Donoho,et al. Higher criticism thresholding: Optimal feature selection when useful features are rare and weak , 2008, Proceedings of the National Academy of Sciences.
[26] David J. Spiegelhalter,et al. Microarrays, Empirical Bayes and the Two-Groups Model. Comment. , 2008 .
[27] Anne-Laure Boulesteix,et al. CMA – a comprehensive Bioconductor package for supervised classification with high dimensional data , 2008, BMC Bioinformatics.
[28] Holger Schwender,et al. Classification with High‐Dimensional Genetic Data: Assigning Patients and Genetic Features to Known Classes , 2008, Biometrical journal. Biometrische Zeitschrift.
[29] Korbinian Strimmer,et al. Gene ranking and biomarker discovery under correlation , 2009, Bioinform..
[30] Ping Xu,et al. Modified linear discriminant analysis approaches for classification of high-dimensional microarray data , 2009, Comput. Stat. Data Anal..
[31] B. Efron. Empirical Bayes Estimates for Large-Scale Prediction Problems , 2009, Journal of the American Statistical Association.
[32] R. Tibshirani,et al. Covariance‐regularized regression and classification for high dimensional problems , 2009, Journal of the Royal Statistical Society. Series B, Statistical methodology.
[33] Korbinian Strimmer,et al. Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks , 2008, J. Mach. Learn. Res..