Multiple Testing of Submatrices of a Precision Matrix With Applications to Identification of Between Pathway Interactions

DOI10.1080/01621459.2016.1251930zbMath1398.62202OpenAlexW2563586581WikidataQ55044223 ScholiaQ55044223MaRDI QIDQ4690961

Tianxi Cai, Yin Xia, T. Tony Cai

Publication date: 23 October 2018

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

Full work available at URL: http://europepmc.org/articles/pmc5988269

zbMATH Keywords

covariance structuremultiple testingfalse discovery ratefalse discovery proportionGaussian graphical modelprecision matrixconditional dependencebetween pathway interactionstesting submatrices

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Hypothesis testing in multivariate analysis (62H15) Paired and multiple comparisons; multiple testing (62J15) Graphical methods in statistics (62A09)

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Uses Software

• Reactome
• IndependenceTests

Cites Work

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• Gaussian graphical model estimation with false discovery rate control
• A consistent characteristic function-based test for conditional independence
• Phase transition and regularized bootstrap in large-scale \(t\)-tests with false discovery rate control
• Regularized rank-based estimation of high-dimensional nonparanormal graphical models
• A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables
• Testing conditional independence using maximal nonlinear conditional correlation
• High-dimensional semiparametric Gaussian copula graphical models
• Nonparametric tests of independence between random vectors
• A NONPARAMETRIC HELLINGER METRIC TEST FOR CONDITIONAL INDEPENDENCE
• A Nonparametric Test of Independence Between Two Vectors
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• A multivariate nonparametric test of independence among many vectors
• Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings
• Testing differential networks with applications to the detection of gene-gene interactions