On the geometric modeling approach to empirical null distribution estimation for empirical Bayes modeling of multiple hypothesis testing.

Baolin Wu

Abstract read

In one paragraph

Article in Computational biology and chemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

Local false discovery rate estimation using feature reliability in LC/MS metabolomics data.Scientific reports · 2015
Article

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5 · Who and what money

Authors and funding

1 author.

Baolin WuDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. baolin@umn.edu

Funding

Statistical Model Building for High Dimensional Biomedical DataR01GM083345 · NIGMS · UNIVERSITY OF MINNESOTA · PI WU, BAOLIN · 2008 to 2011

$1.0M

Statistical methods for large-scale significance and prediction analysis with appR01CA134848 · NCI · UNIVERSITY OF MINNESOTA · PI WU, BAOLIN · 2009 to 2010

$291k

INTEGRATION AND BIOTECHNOLOGY LEADERSHIPT32GM008345 · NIGMS · UNIVERSITY OF COLORADO AT BOULDER · PI DAVIS, ROBERT H. · 1989 to 1997

–

NCI NIH HHS CA134848NCI NIH HHS R01 CA134848NIGMS NIH HHS GM08.345NIGMS NIH HHS R01 GM083345

6 · The paper itself

Abstract

We study the geometric modeling approach to estimating the null distribution for the empirical Bayes modeling of multiple hypothesis testing. The commonly used method is a nonparametric approach based on the Poisson regression, which however could be unduly affected by the dependence among test statistics and perform very poorly under strong dependence. In this paper, we explore a finite mixture model based geometric modeling approach to empirical null distribution estimation and multiple hypothesis testing. Through simulations and applications to two public microarray data, we will illustrate its competitive performance.

Indexed as

Bayes TheoremModels, StatisticalComputer SimulationHumansLeukemiaMaleOligonucleotide Array Sequence AnalysisProstatic Neoplasms

Identifiers

PMID23314152

DOI10.1016/j.compbiolchem.2012.12.001

PMCPMC3580033

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.