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A fundamental task in the analysis of datasets with many variables is screening for associations.
Il calcolo delle assicurazioni su gruppi di teste
Carlo E Bonferroni · 1935
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Anton Schick · 1986
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Yoav Benjamini and Yosef Hochberg · 1995
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Yoav Benjamini and Yosef Hochberg · 1997
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AW van der Vaart · 2000
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The control of the false discovery rate in multiple testing under dependency
Yoav Benjamini and Daniel Yekutieli · 2001
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Empirical Bayes analysis of a microarray experiment
Bradley Efron, Robert Tibshirani, John D Storey, and Virginia Tusher · 2001
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Significance analysis of microarrays applied to the ionizing radiation response
Virginia Goss Tusher, Robert Tibshirani, and Gilbert Chu · 2001
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A mixture model approach for the analysis of microarray gene expression data
David B Allison, Gary L Gadbury, Moonseong Heo, José R Fernández, Cheol-Koo Lee, Tomas A Prolla, and Richard Weindruch · 2002
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The common optimization interface for operations research: Promoting open-source software in the operations research community
Robin Lougee-Heimer · 2003
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The positive false discovery rate: A Bayesian interpretation and the q-value
John D Storey · 2003
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A stochastic process approach to false discovery control
Christopher Genovese and Larry Wasserman · 2004
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Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach
John D Storey, Jonathan E Taylor, and David Siegmund · 2004
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Testing Statistical Hypotheses
EL Lehmann and JP Romano · 2005
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False discovery control with p-value weighting
Christopher R Genovese, Kathryn Roeder, and Larry Wasserman · 2006
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Multidimensional local false discovery rate for microarray studies
Alexander Ploner, Stefano Calza, Arief Gusnanto, and Yudi Pawitan · 2006
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A method to increase the power of multiple testing procedures through sample splitting
Daniel Rubin, Sandrine Dudoit, and Mark Van der Laan · 2006
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Stratified false discovery control for large-scale hypothesis testing with application to genome-wide association studies
Lei Sun, Radu V Craiu, Andrew D Paterson, and Shelley B Bull · 2006
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Improving power in genome-wide association studies: weights tip the scale
Kathryn Roeder, Bernie Devlin, and Larry Wasserman · 2007
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The optimal discovery procedure: a new approach to simultaneous significance testing
John D Storey · 2007
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Oracle and adaptive compound decision rules for false discovery rate control
Wenguang Sun and T Tony Cai · 2007
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Comment: Microarrays, empirical Bayes and the two-groups model
Yoav Benjamini · 2008
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Two simple sufficient conditions for FDR control
Gilles Blanchard and Etienne Roquain · 2008
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Simultaneous inference: When should hypothesis testing problems be combined?
Bradley Efron · 2008
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Unsupervised empirical Bayesian multiple testing with external covariates
Egil Ferkingstad, Arnoldo Frigessi, Håvard Rue, Gudmar Thorleifsson, and Augustine Kong · 2008
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A general framework for multiple testing dependence
Jeffrey T Leek and John D Storey · 2008
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Simultaneous testing of grouped hypotheses: Finding needles in multiple haystacks
T Tony Cai and Wenguang Sun · 2009
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
T Hastie, R Tibshirani, and J Friedman · 2009
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Genome-wide significance levels and weighted hypothesis testing
Kathryn Roeder and Larry Wasserman · 2009
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Optimal weighting for false discovery rate control
Etienne Roquain and Mark Van De Wiel · 2009
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Large-scale multiple testing under dependence
Wenguang Sun and T Tony Cai · 2009
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Independent filtering increases detection power for high-throughput experiments
Richard Bourgon, Robert Gentleman, and Wolfgang Huber · 2010
Data-driven hypothesis weighting increases detection power in genome-scale multiple testing
Nikolaos Ignatiadis, Bernd Klaus, Judith B Zaugg, and Wolfgang Huber · 2016
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Better prediction by use of co-data: adaptive group-regularized ridge regression
Mark A van De Wiel, Tonje G Lien, Wina Verlaat, Wessel N van Wieringen, and Saskia M Wilting · 2016
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Distribution-free multiple testing
Ery Arias-Castro and Shiyun Chen · 2017
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Double/debiased machine learning for treatment and structural parameters
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Large-scale inference: Empirical Bayes methods for estimation, testing, and prediction
Bradley Efron · 2010
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False discovery rate control with groups
James X Hu, Hongyu Zhao, and Harrison H Zhou · 2010
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Tackling the widespread and critical impact of batch effects in high-throughput data
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A censored beta mixture model for the estimation of the proportion of non-differentially expressed genes
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Balanced control of generalized error rates
Joseph P Romano and Michael Wolf · 2010
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A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies
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Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease
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