A statistical framework for testing functional categories in microarray data

DOI10.1214/07-AOAS146SUPPBzbMath1137.62390arXiv0803.3881MaRDI QIDQ2482980

William T. Barry, Fred A. Wright, Andrew B. Nobel

Publication date: 30 April 2008

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0803.3881

zbMATH Keywords

bootstrapdifferential expressionpowertype I errorarray permutation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40) Genetics and epigenetics (92D10)

Related Items (7)

A high-dimensional two-sample test for the mean using random subspaces ⋮ An Empirical Bayesian Approach for Identifying Differential Coexpression in High-Throughput Experiments ⋮ Test-statistic correlation and data-row correlation ⋮ A statistical framework for testing functional categories in microarray data ⋮ Statistical and Knowledge Supported Visualization of Multivariate Data ⋮ Pathway analysis for RNA-Seq data using a score-based approach ⋮ A multi-functional analyzer uses parameter constraints to improve the efficiency of model-based gene-set analysis

Uses Software

• GOstat
• GSA
• GoSurfer
• sma

Cites Work

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• On testing the significance of sets of genes
• Bootstrap methods: another look at the jackknife
• A statistical framework for testing functional categories in microarray data
• Significance analysis of microarrays applied to the ionizing radiation response
• Multiple tests of association with biological annotation metadata
• Better Bootstrap Confidence Intervals
• Effect of Dependence on the Level of Some One-Sample Tests
• Detecting differential gene expression with a semiparametric hierarchical mixture method

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