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Journal Article

Local and Covariate-modulated False Discovery Rates Applied in Neuroimaging


Lawyer,  Glenn
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

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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.

Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-1A2E-8
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.