Journal Article10.1016/J.CSDA.2010.06.017
A generalized false discovery rate in microarray studies
Moonsu Kang,Heuiju Chun +1 more
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TL;DR: The purpose of this paper is to address very large multiplicity problems by adopting a proposed k-FDR controlling procedure under suitable dependence structures and based on a Poisson distributional approximation in a unified framework.
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About: This article is published in Computational Statistics & Data Analysis. The article was published on 01 Jan 2011. The article focuses on the topics: False discovery rate & Multiple comparisons problem.
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Citations
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A practical method to screen and identify functioning biomarkers in nasopharyngeal carcinoma.
Chengyou Liu,Peijie Guo,Leilei Zhou,Yuhe Wang,Shuchang Tian,Yong Ding,Jing Wu,Junlin Zhu,Yu Wang +8 more
TL;DR: In this paper, the authors developed a new method to improve the accuracy of identifying key biomarkers, namely Unit Gamma Measurement (UGM), accounting for multiple hypotheses test statistics distribution, which could reduce the dependency problem.
References
Controlling the false discovery rate: a practical and powerful approach to multiple testing
Yoav Benjamini,Yosef Hochberg +1 more
TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Todd R. Golub,Todd R. Golub,Donna K. Slonim,Pablo Tamayo,Christine Huard,Michelle Gaasenbeek,Jill P. Mesirov,Hilary A. Coller,Mignon L. Loh,James R. Downing,Michael A. Caligiuri,Clara D. Bloomfield,Eric S. Lander +12 more
TL;DR: A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
Significance analysis of microarrays applied to the ionizing radiation response
TL;DR: A method that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements is described, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.
A direct approach to false discovery rates
TL;DR: The calculation of the q‐value is discussed, the pFDR analogue of the p‐value, which eliminates the need to set the error rate beforehand as is traditionally done, and can yield an increase of over eight times in power compared with the Benjamini–Hochberg FDR method.
Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach
TL;DR: In this article, it was shown that the goal of the two approaches are essentially equivalent, and that the FDR point estimates can be used to define valid FDR controlling procedures in both finite sample and asymptotic settings.
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