Arrow plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on sample subgroups
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Maria Antónia Amaral Turkman | Lisete Sousa | Carina Silva-Fortes | M. A. Turkman | L. Sousa | Carina Silva-Fortes
[1] Wolfgang Huber,et al. Antisense expression increases gene expression variability and locus interdependency , 2011, Molecular systems biology.
[2] Henry F. Inman,et al. The overlapping coefficient as a measure of agreement between probability distributions and point estimation of the overlap of two normal densities , 1989 .
[3] Walter Krämer,et al. Review of Modern applied statistics with S, 4th ed. by W.N. Venables and B.D. Ripley. Springer-Verlag 2002 , 2003 .
[4] J. Hanley,et al. The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.
[5] Ian B. Jeffery,et al. Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data , 2006, BMC Bioinformatics.
[6] J. Davis. Bioinformatics and Computational Biology Solutions Using R and Bioconductor , 2007 .
[7] Ash A. Alizadeh,et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling , 2000, Nature.
[8] S. Dudoit,et al. Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data , 2002 .
[9] Gordon K. Smyth,et al. limma: Linear Models for Microarray Data , 2005 .
[10] P. J. Green,et al. Density Estimation for Statistics and Data Analysis , 1987 .
[11] Marco Muselli,et al. Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments , 2008, BMC Bioinformatics.
[12] M. Rosenblatt. Remarks on Some Nonparametric Estimates of a Density Function , 1956 .
[13] Mario Medvedovic,et al. Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments , 2006, BMC Bioinformatics.
[14] Wolfgang Huber,et al. Genome-wide analysis of mRNA decay patterns during early Drosophila development , 2010, Genome Biology.
[15] M. Muselli,et al. ROC curves are a suitable and flexible tool for the analysis of gene expression profiles , 2003, Cytogenetic and Genome Research.
[16] Wolfgang Huber,et al. Genome-wide survey of post-meiotic segregation during yeast recombination , 2011, Genome Biology.
[17] R. Tibshirani,et al. Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[18] Wolfgang Huber,et al. Mapping of signaling networks through synthetic genetic interaction analysis by RNAi , 2011, Nature Methods.
[19] K S Berbaum,et al. A contaminated binormal model for ROC data: Part I. Some interesting examples of binormal degeneracy. , 2000, Academic radiology.
[20] Koji Kadota,et al. A weighted average difference method for detecting differentially expressed genes from microarray data , 2008, Algorithms for Molecular Biology.
[21] M. Pepe. The Statistical Evaluation of Medical Tests for Classification and Prediction , 2003 .
[22] William N. Venables,et al. Modern Applied Statistics with S , 2010 .
[23] Li Li,et al. PADGE: analysis of heterogeneous patterns of differential gene expression. , 2007, Physiological genomics.
[24] C. Metz,et al. "Proper" Binormal ROC Curves: Theory and Maximum-Likelihood Estimation. , 1999, Journal of mathematical psychology.
[25] D. Bamber. The area above the ordinal dominance graph and the area below the receiver operating characteristic graph , 1975 .
[26] Rafael A. Irizarry,et al. Bioinformatics and Computational Biology Solutions using R and Bioconductor , 2005 .
[27] M. Schummer,et al. Selecting Differentially Expressed Genes from Microarray Experiments , 2003, Biometrics.
[28] Kevin S. Berbaum,et al. A contaminated binormal model for ROC data , 2000 .
[29] RAINER BREITLING,et al. Rank-based Methods as a Non-parametric Alternative of the T-statistic for the Analysis of Biological Microarray Data , 2005, J. Bioinform. Comput. Biol..