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Combining meta- and mega- analytic approaches for multi-site diffusion imaging based genetic studies: From the ENIGMA-DTI working group., , , , , , , , , and 27 other author(s). ISBI, page 1234-1238. IEEE, (2014)ENIGMA-Viewer: Interactive Visualization Strategies for Conveying Effect Sizes in Meta-Analysis., , , , , and . BCB, page 640-648. ACM, (2016)On the genetic architecture of cortical folding and brain volume in primates., , , , , , , , , and . NeuroImage, 53 (3): 1103-1108 (2010)On study design in neuroimaging heritability analyses., , , , , , , , , and . Medical Imaging: Image Processing, volume 9034 of SPIE Proceedings, page 90342P. SPIE, (2014)Genetic analysis of cortical sulci in 1, 009 adults., , , , , , , , , and . ISBI, page 833-837. IEEE, (2016)Medial demons registration localizes the degree of genetic influence over subcortical shape variability: An N= 1480 meta-analysis., , , , , , and . ISBI, page 1402-1406. IEEE, (2015)Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies., , , , , , , and . NeuroImage, 53 (3): 1135-1146 (2010)Heritability estimates on resting state fMRI data using the ENIGMA analysis pipeline., , , , , , , , , and 4 other author(s). PSB, page 307-318. (2018)ENIGMA-Viewer: interactive visualization strategies for conveying effect sizes in meta-analysis., , , , , , , and . BMC Bioinform., 18 (6): 17-29 (2017)Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA., , , , , , , , , and 9 other author(s). NeuroImage, (2020)