Multiple testing approaches for hypotheses in integrative genomics

Cites Work

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Estimating the proportion of false null hypotheses among a large number of independently tested hypotheses
Hypothesis setting and order statistic for robust genomic meta-analysis
Testing the disjunction hypothesis using Voronoi diagrams with applications to genetics
The sequential rejection principle of familywise error control
A systematic comparison of methods for combining \(p\)-values from independent tests
Causal graphical models in systems genetics: a unified framework for joint inference of causal network and genetic architecture for correlated phenotypes
Empirical null and false discovery rate inference for exponential families
Robustness of multiple testing procedures against dependence
A simple forward selection procedure based on false discovery rate control
On the false discovery rate and an asymptotically optimal rejection curve
An adaptive step-down procedure with proven FDR control under independence
Resampling-based multiple testing for microarray data analysis (With comments)
Bioequivalence trials, intersection-union tests and equivalence confidence sets. With comments and a rejoinder by the authors
The control of the false discovery rate in multiple testing under dependency.
Some results on false discovery rate in stepwise multiple testing procedures.
A stochastic process approach to false discovery control.
A combined \(p\)-value test for multiple hypothesis testing
False discovery rate control with multivariate \(p\)-values
Optimal weighting for false discovery rate control
Unsupervised empirical Bayesian multiple testing with external covariates
Joint analysis of SNP and gene expression data in genetic association studies of complex diseases
Dependency and false discovery rate: asymptotics
On false discovery control under dependence
Simultaneous inference: when should hypothesis testing problems be combined?
False discovery and false nondiscovery rates in single-step multiple testing procedures
Generalizations of the familywise error rate
Hierarchical testing designs for pattern recognition
Adaptive FDR control under independence and dependence
Large-Scale Multiple Testing under Dependence
Multiple Comparisons Among Means
Adaptive linear step-up procedures that control the false discovery rate
False discovery control with p-value weighting
Screening for Partial Conjunction Hypotheses
Controlling False Discoveries in Multidimensional Directional Decisions, with Applications to Gene Expression Data on Ordered Categories
Oracle and Adaptive Compound Decision Rules for False Discovery Rate Control
False Discovery Rates for Spatial Signals
Hierarchical False Discovery Rate–Controlling Methodology
A sharper Bonferroni procedure for multiple tests of significance
Empirical Bayes Analysis of a Microarray Experiment
Weighted False Discovery Rate Control in Large-Scale Multiple Testing
Controlling the Familywise Error Rate with Plug-in Estimator for the Proportion of True Null Hypotheses
Discovering the False Discovery Rate
Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach
A Note on the Adaptive Control of False Discovery Rates
A Direct Approach to False Discovery Rates
An improved Bonferroni procedure for multiple tests of significance
False Discovery Rate Control With Groups
Multiple Testing for Pattern Identification, With Applications to Microarray Time-Course Experiments
Shrunken p‐Values for Assessing Differential Expression with Applications to Genomic Data Analysis
Estimating the Null and the Proportion of Nonnull Effects in Large-Scale Multiple Comparisons
Correlation and Large-Scale Simultaneous Significance Testing
Variance of the Number of False Discoveries
The p-filter: Multilayer False Discovery Rate Control for Grouped Hypotheses
Some Results on the Control of the False Discovery Rate under Dependence
Some Concepts of Dependence
Rectangular Confidence Regions for the Means of Multivariate Normal Distributions
A General Framework for Weighted Gene Co-Expression Network Analysis
Selective Inference on Multiple Families of Hypotheses
Moving to a World Beyond “p < 0.05”
The ASA Statement on p-Values: Context, Process, and Purpose

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