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  Local and Covariate-modulated False Discovery Rates Applied in Neuroimaging

Lawyer, G., Ferkingstad, E., Nesvågc, R., Varnäsd, K., & Agartz, I. (2009). Local and Covariate-modulated False Discovery Rates Applied in Neuroimaging. NeuroImage, 47(1), 213-219. doi:10.1016/j.neuroimage.2009.03.047.

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 Creators:
Lawyer, Glenn1, Author           
Ferkingstad, Egil2, Author
Nesvågc, Ragnar2, Author
Varnäsd, Katarina2, Author
Agartz, Ingrid2, Author
Affiliations:
1Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046              
2External Organizations, ou_persistent22              

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 Abstract: False discovery rate (FDR) control has become a standard technique in neuroimaging. Recent work has shown that a finer grained estimate of the FDR is obtained by estimating, at a specific value of the test statistic, the scaled ratio of the null density to the observed density of the test statistic. The method can be extended by allowing an external covariate, also measured on the points where the hypothesis was tested, to modulate estimation of this local FDR. The current work, in addition to demonstrating these methods by re-analyzing results from two previously published investigations of cortical thickness, presents a method to test if the covariate modulation differs significantly from chance. The first study compared schizophrenia patients to healthy controls and the second compared genotypes of the -633 T/A polymorphism of the gene coding the brain derived neurotrophic factor (BDNF) protein in a subset of the subjects from the case/control study. Local FDR estimates increased findings over FDR in both studies. Using p-values from the case/control study to modulate local FDR estimation in the BDNF study further increased findings. The relationship between case/control related and BDNF related cortical thickness variation was found to be highly significant, providing support for this gene's involvement in the etiology of the disease. The increased statistical precision from more accurate models of the distribution of the test statistic demonstrates the potential of these methods for neuroimaging and suggests the possibility to test novel hypothesis.

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Language(s): eng - English
 Dates: 2010-01-1220092009
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: eDoc: 520892
BibTex Citekey: Lawyer2009_lFDR
DOI: 10.1016/j.neuroimage.2009.03.047
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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Amsterdam : Elsevier
Pages: - Volume / Issue: 47 (1) Sequence Number: - Start / End Page: 213 - 219 Identifier: ISSN: 1053-8119