A semi-parametric approach for mixture models: Application to local false discovery rate estimation

[1]  L. B. Jones,et al.  A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays , 2006, Bioinform..

[2]  J. Daudin,et al.  Mixture model on the variance for the differential analysis of gene expression data , 2005 .

[3]  Weichung Joe Shih,et al.  A mixture model for estimating the local false discovery rate in DNA microarray analysis , 2004, Bioinform..

[4]  Jean-Jacques Daudin,et al.  Determination of the differentially expressed genes in microarray experiments using local FDR , 2004, BMC Bioinformatics.

[5]  Charles C. Taylor,et al.  Boosting kernel density estimates: A bias reduction technique? , 2004 .

[6]  Lasse Holmström,et al.  A semiparametric density estimation approach to pattern classification , 2004, Pattern Recognit..

[7]  B. Efron Large-Scale Simultaneous Hypothesis Testing , 2004 .

[8]  John D. Storey,et al.  Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach , 2004 .

[9]  Alexander Isaev,et al.  PyEvolve: a toolkit for statistical modelling of molecular evolution , 2004, BMC Bioinformatics.

[10]  John D. Storey,et al.  Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Stan Pounds,et al.  Estimating the Occurrence of False Positives and False Negatives in Microarray Studies by Approximating and Partitioning the Empirical Distribution of P-values , 2003, Bioinform..

[12]  L. Wasserman,et al.  Operating characteristics and extensions of the false discovery rate procedure , 2002 .

[13]  David B. Allison,et al.  A mixture model approach for the analysis of microarray gene expression data , 2002 .

[14]  John D. Storey,et al.  Empirical Bayes Analysis of a Microarray Experiment , 2001 .

[15]  E. Dougherty,et al.  Gene-expression profiles in hereditary breast cancer. , 2001, The New England journal of medicine.

[16]  C. Priebe,et al.  Alternating kernel and mixture density estimates , 2000 .

[17]  G. McLachlan,et al.  Finite Mixture Models , 2000, Wiley Series in Probability and Statistics.

[18]  R. Tibshirani,et al.  Using specially designed exponential families for density estimation , 1996 .

[19]  N. Hjort,et al.  Nonparametric Density Estimation with a Parametric Start , 1995 .

[20]  Ingram Olkin,et al.  A Semiparametric Approach to Density Estimation , 1987 .

[21]  Gordon K Smyth,et al.  Statistical Applications in Genetics and Molecular Biology Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments , 2011 .

[22]  M. Rudemo,et al.  Variance models for microarray data , 2002 .

[23]  Christopher R. Genovese,et al.  Operating Characteristics and Extensions of the FDR Procedure , 2001 .

[24]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .