Multiple Hypothesis Testing

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Resampling-based empirical Bayes multiple testing procedures for controlling generalized tail probability and expected value error rates: Focus on the false discovery rate and simulation stud (with Houston N. Gilbert and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2007)

This article proposes resampling-based empirical Bayes multiple testing procedures for controlling a broad class of...

 

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A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting (with Daniel Rubin and Mark van der Laan), Statistical Applications in Genetics and Molecular Biology (2006)

Consider the standard multiple testing problem where many hypotheses are to be tested, each hypothesis...

 

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A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting (with Daniel Rubin, Sandrine Dudoit, and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2006)

Consider the standard multiple testing problem where many hypotheses are to be tested, each hypothesis...

 

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Test statistics null distributions in multiple testing: Simulation studies and applications to genomics (with Katherine S. Pollard, Merrill D. Birkner, and Mark J. van der Laan), Journal de la Société Française de Statistique (2005)

Multiple hypothesis testing problems arise frequently in biomedical and genomic research, for instance, when identifying...

 

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Test Statistics Null Distributions in Multiple Testing: Simulation Studies and Applications to Genomics (with Katherine S. Pollard, Merrill D. Birkner, and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2005)

Multiple hypothesis testing problems arise frequently in biomedical and genomic research, for instance, when identifying...

 

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Multiple Testing Procedures and Applications to Genomics (with Merrill D. Birkner, Katherine S. Pollard, and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2005)

This chapter proposes widely applicable resampling-based single-step and stepwise multiple testing procedures (MTP) for controlling...

 

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Multiple Testing Procedures for Controlling Tail Probability Error Rates (with Mark J. van der Laan and Merrill D. Birkner), U.C. Berkeley Division of Biostatistics Working Paper Series (2004)

The present article discusses and compares multiple testing procedures (MTP) for controlling Type I error...

 

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Augmentation Procedures for Control of the Generalized Family-Wise Error Rate and Tail Probabilities for the Proportion of False Positives (with Mark J. van der Laan and Katherine S. Pollard), Statistical Applications in Genetics and Molecular Biology (2004)

This article shows that any single-step or stepwise multiple testing procedure (asymptotically) controlling the family-wise...

 

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Multiple Testing. Part II. Step-Down Procedures for Control of the Family-Wise Error Rate (with Mark J. van der Laan and Katherine S. Pollard), Statistical Applications in Genetics and Molecular Biology (2004)

The present article proposes two step-down multiple testing procedures for asymptotic control of the family-wise...

 

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Multiple Testing. Part I. Single-Step Procedures for Control of General Type I Error Rates (with Mark J. van der Laan and Katherine S. Pollard), Statistical Applications in Genetics and Molecular Biology (2004)

The present article proposes general single-step multiple testing procedures for controlling Type I error rates...

 

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Multiple Testing. Part III. Procedures for Control of the Generalized Family-Wise Error Rate and Proportion of False Positives (with Mark J. van der Laan and Katherine S. Pollard), U.C. Berkeley Division of Biostatistics Working Paper Series (2004)

The accompanying articles by Dudoit et al. (2003b) and van der Laan et al. (2003)...

 

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Multiple Testing. Part II. Step-Down Procedures for Control of the Family-Wise Error Rate (with Mark J. van der Laan and Katherine S. Pollard), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

The present article proposes two step-down multiple testing procedures for asymptotic control of the family-wise...

 

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Multiple Testing. Part I. Single-Step Procedures for Control of General Type I Error Rates (with Mark J. van der Laan and Katherine S. Pollard), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

The present article proposes general single-step multiple testing procedures for controlling Type I error rates...

 

Loss-Based Estimation with Cross-Validation

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A deletion/substitution/addition algorithm for classification neural networks, with applications to biomedical data (with Blythe Durbin and Mark J. van der Laan), Journal of Statistical Planning and Inference (2008)

Neural networks are a popular machine learning tool, particularly in applications such as protein structure...

 

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Loss-based estimation with evolutionary algorithms and cross-validation (with David Shilane and Richard H. Liang), U.C. Berkeley Division of Biostatistics Working Paper Series (2007)

Many statistical inference methods rely upon selection procedures to estimate a parameter of the joint...

 

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Survival Ensembles (with Torsten Hothorn, Peter Buhlmann, Annette M. Molinaro, and Mark J. van der Laan), Biostatistics (2006)

We propose a unified and flexible framework for ensemble learning in the presence of censoring....

 

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Oracle inequalities for multi-fold cross validation (with Aad W. van der Vaart and Mark J. van der Laan), Statistics & Decisions (2006)

We consider choosing an estimator or model from a given class by cross validation consisting...

 

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The cross-validated adaptive epsilon-net estimator (with Mark J. van der Laan and Aad W. van der Vaart), Statistics & Decisions (2006)

Suppose that we observe a sample of independent and identically distributed realizations of a random...

 

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Asymptotics of cross-validated risk estimation in estimator selection and performance assessment (with Mark J. van der Laan), Statistical Methodology (2005)

Risk estimation is an important statistical question for the purposes of selecting a good estimator...

 

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Survival Ensembles (with Torsten Hothorn, Peter Buhlmann, Annette M. Molinaro, and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2005)

We propose a unified and flexible framework for ensemble learning in the presence of censoring....

 

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Optimization of the Architecture of Neural Networks Using a Deletion/Substitution/Addition Algorithm (with Blythe Durbin and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2005)

Neural networks are a popular machine learning tool, particularly in applications such as the prediction...

 

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Asymptotic Optimality of Likelihood-Based Cross-Validation (with Mark J. van der Laan and Sunduz Keles), Statistical Applications in Genetics and Molecular Biology (2004)

Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d....

 

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The Cross-Validated Adaptive Epsilon-Net Estimator (with Mark J. van der Laan and Aad W. van der Vaart), U.C. Berkeley Division of Biostatistics Working Paper Series (2004)

Suppose that we observe a sample of independent and identically distributed realizations of a random...

 

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Loss-Based Estimation with Cross-Validation: Applications to Microarray Data Analysis and Motif Finding (with Mark J. van der Laan, Sunduz Keles, Annette M. Molinaro, Sandra E. Sinisi, and Siew Leng Teng), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

Current statistical inference problems in genomic data analysis involve parameter estimation for high-dimensional multivariate distributions,...

 

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Unified Cross-Validation Methodology For Selection Among Estimators and a General Cross-Validated Adaptive Epsilon-Net Estimator: Finite Sample Oracle Inequalities and Examples (with Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

In Part I of this article we propose a general cross-validation criterian for selecting among...

 

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Asymptotically Optimal Model Selection Method with Right Censored Outcomes (with Sunduz Keles and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

Over the last two decades, non-parametric and semi-parametric approaches that adapt well known techniques such...

 

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Tree-based Multivariate Regression and Density Estimation with Right-Censored Data (with Annette M. Molinaro and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

We propose a unified strategy for estimator construction, selection, and performance assessment in the presence...

 

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Asymptotic Optimality of Likelihood Based Cross-Validation (with Mark J. van der Laan and Sunduz Keles), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d....

 

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Asymptotics of Cross-Validated Risk Estimation in Estimator Selection and Performance Assessment (with Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

Risk estimation is an important statistical question for the purposes of selecting a good estimator...

 

Statistical Computing

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Multiple Testing Procedures: R multtest Package and Applications to Genomics (with Katherine S. Pollard and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2004)

The Bioconductor R package multtest implements widely applicable resampling-based single-step and stepwise multiple testing procedures...

 

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Bioconductor: open software development for computational biology and bioinformatics (with Robert C. Gentleman, Vincent J. Carey, Douglas M. Bates, Ben Bolstad, Marcel Dettling, Byron Ellis, Laurent Gautier, Yongchao Ge, Jeff Gentry, Kurt Hornik, Torsten Hothorn, Wolfgang Huber, Stefano Iacus, Rafael Irizarry, Friedrich Leisch, Cheng Li, Martin Maechler, Anthony J. Rossini, Gunther Sawitzki, Colin Smith, Gordon Smyth, Luke Tierney, Jean Y. H. Yang, and Jianhua Zhang), Genome Biology (2004)

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational...

 

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Bioconductor: Open software development for computational biology and bioinformatics (with Robert C. Gentleman, Vincent J. Carey, Douglas J. Bates, Benjamin M. Bolstad, Marcel Dettling, Byron Ellis, Laurent Gautier, Yongchao Ge, Jeff Gentry, Kurt Hornik, Torsten Hothorn, Wolfgang Huber, Stefano Iacus, Rafael Irizarry, Friedrich Leisch, Cheng Li, Martin Maechler, Anthony J. Rossini, Guenther Sawitzki, Colin Smith, Gordon K. Smyth, Luke Tierney, Yee Hwa Yang, and Jianhua Zhang), Bioconductor Project Working Papers (2004)

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational...

 

Genetic Mapping

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A Fine-Scale Linkage-Disequilibrium Measure Based on Length of Haplotype Sharing (with Yan Wang and Lue Ping Zhao), The American Journal of Human Genetics (2006)

High-throughput genotyping technologies for SNPs have enabled the recent completion of the International HapMap Project...

 

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A Fine-Scale Linkage Disequilibrium Measure Based on Length of Haplotype Sharing (with Yan Wang and Lue Ping Zhao), U.C. Berkeley Division of Biostatistics Working Paper Series (2005)

High-throughput genotyping technologies for single nucleotide polymorphisms (SNP) have enabled the recent completion of the...

 

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Quantification and Visualization of LD Patterns and Identification of Haplotype Blocks (with Yan Wang), U.C. Berkeley Division of Biostatistics Working Paper Series (2004)

Classical measures of linkage disequilibrium (LD) between two loci, based only on the joint distribution...

 

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IBD Configuration Transition Matrices and Linkage Score Tests for Unilineal Relative Pairs, U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

Properties of transition matrices between IBD configurations are derived for four general classes of unilineal...

 

Biological Sequence Analysis

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Supervised Detection of Regulatory Motifs in DNA Sequences (with Sunduz Keles, Mark J. van der Laan, Biao Xing, and Michael B. Eisen ), Statistical Applications in Genetics and Molecular Biology (2003)

Identification of transcription factor binding sites (regulatory motifs) is a major interest in contemporary biology....

 

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Supervised Detection of Regulatory Motifs in DNA Sequences (with Sunduz Keles, Mark J. van der Laan, Biao Xing, and Michael B. Eisen), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)

Identification of transcription factor binding sites (regulatory motifs) is a major interest in contemporary biology....

 

Microarray Data Analysis

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Prognosis of stage II colon cancer by non-neoplastic mucosa gene expression profiling (with A. Barrier, F. Roser, P-Y. Boelle, B. Franc, C. Tse, D. Brault, F. Lacaine, S. Houry, P. Callard, C. Penna, B. Debuire, A. Flahault, and A. Lemoine), Oncogene (2007)

We have assessed the possibility to build a prognosis predictor (PP), based on non-neoplastic mucosa...

 

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Stage II Colon Cancer Prognosis Prediction by Tumor Gene Expression Profiling (with Alain Barrier, Pierre-Yves Boelle, François Roser, Jennifer Gregg, Chantal Tse, Didier Brault, François Lacaine, Sidney Houry, Michel Huguier, Brigitte Franc, Antoine Flahault, and Antoinette Lemoine), Journal of Clinical Oncology (2006)

PURPOSE: This study mainly aimed to identify and assess the performance of a microarray-based prognosis...

 

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Multiple Testing Methods For ChIP–Chip High Density Oligonucleotide Array Data (with Sündüz Keleş, Mark J. van der Laan, and Simon E. Cawley), Journal of Computational Biology (2006)

Cawley et al. (2004) have recently mapped the locations of binding sites for three transcription...

 

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Exploration of global gene expression in human liver steatosis by high-density oligonucleotide microarray (with Frank Chiappini, Alain Barrier, Raphaël Saffroy, Marie-Charlotte Domart, Nicolas Dagues, Daniel Azoulay, Mylène Sebagh, Brigitte Franc, Stephan Chevalier, Brigitte Debuire, and Antoinette Lemoine), Laboratory Investigation (2005)

Understanding the molecular mechanisms underlying fatty liver disease (FLD) in humans is of major importance....

 

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Gene expression profiling of nonneoplastic mucosa may predict clinical outcome of colon cancer patients (with Alain Barrier, Pierre-Yves Boelle, Antoinette Lemoine, Chantal Tse, Didier Brault, Frank Chiappini, François Lacaine, Sidney Houry, Michel Huguier, and Antoine Flahault), Diseases of the Colon and Rectum (2005)

PURPOSE This study assessed the possibility to build a prognosis predictor, based on microarray gene...

 

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Ischemic preconditioning modulates the expression of several genes, leading to the overproduction of IL-1Ra, iNOS, and Bcl-2 in a human model of liver ischemia-reperfusion (with Alain Barrier, Natalia Olaya, Franck Chiappini, François Roser, Olivier Scatton, Cédric Artus, Brigitte Franc, Antoine Flahault, Brigitte Debuire, Daniel Azoulay, and Antoinette Lemoine), The FASEB Journal (2005)

Ischemia triggers an inflammatory response that precipitates cell death during reperfusion. Several studies have shown...

 

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Colon cancer prognosis prediction by gene expression profiling (with Alain Barrier, Antoinette Lemoine, Pierre-Yves Boelle, Chantal Tse, Didier Brault, Franck Chiappini, Julia Breittschneider, François Lacaine, Sidney Houry, Michel Huguier, Mark J. van der Laan, Terry Speed, Brigitte Debuire, and Antoine Flahault), Oncogene (2005)

This study assessed the possibility to build a prognosis predictor, based on microarray gene expression...

 

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Colon Cancer Prognosis Prediction by Gene Expression Profiling (with Alain Barrier and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2005)

Aims. This study assessed the possibility to build a prognosis predictor, based on microarray gene...

 

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Prognosis of Stage II Colon Cancer by Non-Neoplastic Mucosa Gene Expresssion Profiling (with Alain Barrier and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2005)

Aims. This study assessed the possibility to build a prognosis predictor, based on non-neoplastic mucosa...

 

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Multiple Testing Methods For ChIP-Chip High Density Oligonucleotide Array Data (with Sunduz Keles, Mark J. van der Laan, and Simon E. Cawley), U.C. Berkeley Division of Biostatistics Working Paper Series (2004)

Cawley et al. (2004) have recently mapped the locations of binding sites for three transcription...

 

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Multiple Hypothesis Testing in Microarray Experiments (with Juliet Popper Shaffer and Jennifer C. Boldrick), U.C. Berkeley Division of Biostatistics Working Paper Series (2002)

DNA microarrays are a new and promising biotechnology which allows the monitoring of expression levels...

 

Biological Annotation Metadata Analysis

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Multiple Tests of Association with Biological Annotation Metadata (with Sunduz Keles and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2006)

We propose a general and formal statistical framework for the multiple tests of associations between...

 

Miscellaneous

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A General Framework for Statistical Performance Comparison of Evolutionary Computation Algorithms (with David Shilane, Jarno Martikainen, and Seppo Ovaska), U.C. Berkeley Division of Biostatistics Working Paper Series (2006)

This paper proposes a statistical methodology for comparing the performance of evolutionary computation algorithms. A...