Large-Scale Simultaneous Hypothesis Testing

DOI10.1198/016214504000000089zbMath1089.62502OpenAlexW1824047490WikidataQ56170498 ScholiaQ56170498MaRDI QIDQ5474408

Efron, Bradley

Publication date: 26 June 2006

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/016214504000000089

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items

Large-Scale Hypothesis Testing for Causal Mediation Effects with Applications in Genome-wide Epigenetic Studies, Detection of Local Differences in Spatial Characteristics Between Two Spatiotemporal Random Fields, Rejoinder: Confidence Intervals for Nonparametric Empirical Bayes Analysis, Testing homogeneity in a heteroscedastic contaminated normal mixture, Heteroscedasticity-Adjusted Ranking and Thresholding for Large-Scale Multiple Testing, Estimating Effect Sizes of Differentially Expressed Genes for Power and Sample-Size Assessments in Microarray Experiments, Estimating the Proportion of True Null Hypotheses in Nonparametric Exponential Mixture Model with Appication to the Leukemia Gene Expression Data, Constrained Bayesian Rules for Testing Statistical Hypotheses, Large-Scale Multiple Testing under Dependence, Maximum Rank Reproducibility: A Nonparametric Approach to Assessing Reproducibility in Replicate Experiments, False Discovery Rate Smoothing, Partial correlation matrix estimation using ridge penalty followed by thresholding and re-estimation, Generalized FWER control procedures for testing multiple hypotheses, Correcting false discovery rates for their bias toward false positives, Joint Mean and Covariance Estimation with Unreplicated Matrix-Variate Data, Uniform consistency in nonparametric mixture models, Constructing confidence intervals for selected parameters, Distributed eQTL analysis with auxiliary information, Testing homogeneity in contaminated mixture models, Penalized maximum likelihood estimator for finite multivariate skew normal mixtures, Adaptive local false discovery rate procedures for highly spiky data and their application RNA sequencing data of yeast SET4 deletion mutants, Two‐group Poisson‐Dirichlet mixtures for multiple testing, A nonparametric mixture approach to density and null proportion estimation in large‐scale multiple comparison problems, Fault classification for high‐dimensional data streams: A directional diagnostic framework based on multiple hypothesis testing, Optimal Estimation of the Number of Network Communities, Double Empirical Bayes Testing, Estimation of the Number of Spiked Eigenvalues in a Covariance Matrix by Bulk Eigenvalue Matching Analysis, Structure–Adaptive Sequential Testing for Online False Discovery Rate Control, Two-Component Mixture Model in the Presence of Covariates, A Flexible and Powerful Bayesian Hierarchical Model for ChIP-Chip Experiments, Nearly optimal Bayesian shrinkage for high-dimensional regression, Unnamed Item, A horseshoe mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging, Individualized risk assessment of preoperative opioid use by interpretable neural network regression, Adaptive novelty detection with false discovery rate guarantee, Revisiting consistency of a recursive estimator of mixing distributions, A general framework for multiple testing dependence, Tuning parameter selection in fused lasso signal approximator with false discovery rate control, Convergence of stochastic approximation algorithms under irregular conditions, Bayesian False Discovery Rate Wavelet Shrinkage: Theory and Applications, F-distribution calibrated empirical likelihood ratio tests for multiple hypothesis testing, Evaluation of false discovery rate and power via sample size in microarray studies, Empirical null distribution-based modeling of multi-class differential gene expression detection, An Efficient Morris Method-Based Framework for Simulation Factor Screening, Estimation and selection in high-dimensional genomic studies for developing molecular diagnostics, Sample size calculations for controlling the distribution of false discovery proportion in microarray experiments, Unifying and Generalizing Methods for Removing Unwanted Variation Based on Negative Controls, On simultaneous calibration of two-sample t-tests for high-dimension low-sample-size data, Estimating the Null Distribution to Adjust Observed Confidence Levels for Genome-Scale Screening, Unnamed Item, Inference on the Order of a Normal Mixture, Integrating Prior Knowledge in Multiple Testing under Dependence with Applications to Detecting Differential DNA Methylation, A multiple testing protocol for exploratory data analysis and the local misclassification rate, A Hierarchical Semiparametric Model for Incorporating Intergene Information for Analysis of Genomic Data, Cross-Dimensional Inference of Dependent High-Dimensional Data, Multiple Testing of Composite Null Hypotheses in Heteroscedastic Models, Large‐scale signal detection: A unified perspective, A Bayesian hierarchical framework for modeling brain connectivity for neuroimaging data, Contaminated normal modeling with application to microarray data analysis, Estimating the False Discovery Rate Using Nonparametric Deconvolution, Density estimation using non-parametric and semi-parametric mixtures, Genome Scanning Tests for Comparing Amino Acid Sequences Between Groups, Model fusion and multiple testing in the likelihood paradigm: shrinkage and evidence supporting a point null hypothesis, Multiple testing for neuroimaging via hidden Markov random field, Exploring the Information in p‐Values for the Analysis and Planning of Multiple‐Test Experiments, Robust Clustering Using Exponential Power Mixtures, AAPL: assessing association between p‐value lists, Theoretical Measures of Relative Performance of Classifiers for High Dimensional Data with Small Sample Sizes, Proportion of Non-Zero Normal Means: Universal Oracle Equivalences and Uniformly Consistent Estimators, Bayesian Robust Inference for Differential Gene Expression in Microarrays with Multiple Samples, Statistical Methods for Expression Quantitative Trait Loci (eQTL) Mapping, FRACTAL CHARACTERIZATIONS OF MAX STATISTICAL DISTRIBUTION IN GENETIC ASSOCIATION STUDIES, False Discovery Rate Based on Extreme Values in High Dimension, Covariate-Assisted Ranking and Screening for Large-Scale Two-Sample Inference, RandomisedP-values and nonparametric procedures in multiple testing, A Bayesian Goodness of Fit Test and Semiparametric Generalization of Logistic Regression with Measurement Data, Constrained Bayesian Method for Testing Multiple Hypotheses in Sequential Experiments, On Fast Computation of the Non-Parametric Maximum Likelihood Estimate of a Mixing Distribution, Finite skew-mixture models for estimation of positive false discovery rates, Null-free false discovery rate control using decoy permutations, A simple yet efficient method of local false discovery rate estimation designed for genome-wide association data analysis, Testing the order of a normal mixture in mean, False discovery rate control with unknown null distribution: is it possible to mimic the oracle?, A review on recent advances and applications of h-likelihood method, Consistency of a recursive estimate of mixing distributions, Hypothesis test for normal mixture models: the EM approach, Empirical Bayes cumulative \(\ell\)-value multiple testing procedure for sparse sequences, Powerful multiple testing of paired null hypotheses using a latent graph model, A Markov random field-based approach for joint estimation of differentially expressed genes in mouse transcriptome data, Extended likelihood approach to multiple testing with directional error control under a hidden Markov random field model, Optimal rates of convergence for estimating the null density and proportion of nonnull effects in large-scale multiple testing, Fast inference of individual admixture coefficients using geographic data, A parametric model to estimate the proportion from true null using a distribution for \(p\)-values, Sparse latent factor regression models for genome-wide and epigenome-wide association studies, A powerful FDR control procedure for multiple hypotheses, Estimating large covariance matrix with network topology for high-dimensional biomedical data, Estimating minimum effect with outlier selection, More nonparametric Bayesian inference in applications, NetMix2: unifying network propagation and altered subnetworks, Detection of two-way outliers in multivariate data and application to cheating detection in educational tests, BOPA: A Bayesian hierarchical model for outlier expression detection, Testing the disjunction hypothesis using Voronoi diagrams with applications to genetics, Detection boundary and higher criticism approach for rare and weak genetic effects, A Bayesian nonparametric mixture model for selecting genes and gene subnetworks, Capturing the severity of type II errors in high-dimensional multiple testing, Microarrays, empirical Bayes and the two-groups model, Comment: ``Microarrays, empirical Bayes and the two-group model, Estimation of empirical null using a mixture of normals and its use in local false discovery rate, The future of indirect evidence, Power-enhanced multiple decision functions controlling family-wise error and false discovery rates, Multiple testing via \(\mathrm{FDR}_L\) for large-scale imaging data, A Bernstein-type estimator for decreasing density with application to \(p\)-value adjustments, The constrained Fisher scoring method for maximum likelihood computation of a nonparametric mixing distribution, Robust test for detecting a signal in a high dimensional sparse normal vector, On efficient calculations for Bayesian variable selection, Asymptotic Bayes-optimality under sparsity of some multiple testing procedures, Bootstrap inference for network construction with an application to a breast cancer microarray study, Frequentist properties of Bayesian multiplicity control for multiple testing of normal means, False discovery rate control with multivariate \(p\)-values, Penalized orthogonal-components regression for large \(p\) small \(n\) data, Multiple hypothesis testing on composite nulls using constrained \(p\)-values, Compound \(p\)-value statistics for multiple testing procedures, Mutual fund performance: false discoveries, bias, and power, A statistical approach to high-throughput screening of predicted orthologs, A novel characterization of the generalized family wise error rate using empirical null distributions, Monotone false discovery rate, Size, power and false discovery rates, Effect-size estimation using semiparametric hierarchical mixture models in disease-association studies with neuroimaging data, A Bayesian nonparametric spiked process prior for dynamic model selection, An empirical Bayes approach for the identification of long-range chromosomal interaction from Hi-C data, Diverse correlation structures in gene expression data and their utility in improving statistical inference, Accounting for spatial correlation in the scan statistic, False discovery variance reduction in large scale simultaneous hypothesis tests, Semiparametric methods for center effect measures based on the ratio of survival functions, Approximate \(\ell_0\)-penalized estimation of piecewise-constant signals on graphs, Estimation and confidence sets for sparse normal mixtures, Internal validation inferences of significant genomic features in genome-wide screening, Balancing type one and two errors in multiple testing for differential expression of genes, A robust unified approach to analyzing methylation and gene expression data, Shrinkage estimation of effect sizes as an alternative to hypothesis testing followed by estimation in high-dimensional biology: applications to differential gene expression, False discovery rate analysis of brain diffusion direction maps, Simultaneous inference: when should hypothesis testing problems be combined?, A mixture modeling framework for differential analysis of high-throughput data, An empirical Bayes mixture method for effect size and false discovery rate estimation, Feature selection in omics prediction problems using cat scores and false nondiscovery rate control, Detecting mutations in mixed sample sequencing data using empirical Bayes, Are a set of microarrays independent of each other?, Two-group classification with high-dimensional correlated data: a factor model approach, Updating of the Gaussian graphical model through targeted penalized estimation, The Generalized Ridge Estimator of the Inverse Covariance Matrix, A cross-validation based estimation of the proportion of true null hypotheses, Nonparametric false discovery rate control for identifying simultaneous signals, Empirical null and false discovery rate inference for exponential families, False Discovery Rate Control Under General Dependence By Symmetrized Data Aggregation, A survey of nonparametric mixing density estimation via the predictive recursion algorithm, Distributions associated with simultaneous multiple hypothesis testing, Ridge estimation of the VAR(1) model and its time series chain graph from multivariate time-course omics data, Empirical Bayes analysis of RNA sequencing experiments with auxiliary information, Evaluating hospital readmission rates in dialysis facilities; adjusting for hospital effects, A new perspective on robust \(M\)-estimation: finite sample theory and applications to dependence-adjusted multiple testing, Generalized linear mixed models with Gaussian mixture random effects: inference and application, Interval estimation in a finite mixture model: Modeling \(P\)-values in multiple testing ap\-plications, Cluster analysis using multivariate normal mixture models to detect differential gene expression with microarray data, Efficient computer experiment-based optimization through variable selection, On-line changepoint detection and parameter estimation with application to genomic data, A Kendall correlation coefficient between functional data, Comparison of Bayesian and frequentist multiplicity correction for testing mutually exclusive hypotheses under data dependence, A semi-parametric approach for mixture models: application to local false discovery rate estimation, Supplementary score test for sparse signals in large-scale truncated one-sided sequential tests, Density estimation with contamination: minimax rates and theory of adaptation, Estimating high-dimensional intervention effects from observational data, Robust nearest-neighbor methods for classifying high-dimensional data, Semi-supervised multiple testing, Flexible estimation of a semiparametric two-component mixture model with one parametric component, Simple estimators of false discovery rates given as few as one or two \(p\)-values without strong parametric assumptions, A Markov random field-based approach to characterizing human brain development using spatial-temporal transcriptome data, Higher criticism for large-scale inference, especially for rare and weak effects, Monte Carlo null models for genomic data