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• W1591939718 endingPage "238" @default.
• W1591939718 startingPage "229" @default.
• W1591939718 abstract "The quest to discover genetic variants that affect the human brain will be accelerated by screening brain images from large populations. Even so, the wealth of information in medical images is often reduced to a single numeric summary, such as a regional volume or an average signal, which is then analyzed in a genome wide association study (GWAS). The high cost and penalty for multiple comparisons often constrains us from searching over the entire image space. Here, we developed a method to compute and boost power to detect genetic associations in brain images. We computed voxel-wise heritability estimates for fractional anisotropy in over 1,100 DTI scans, and used the results to threshold FA images from new studies. We describe voxel selection criteria to optimally boost power, as a function of the sample size and allele frequency cut-off. We illustrate our methods by analyzing publicly-available data from the ADNI2 project." @default.
• W1591939718 created "2016-06-24" @default.
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• W1591939718 date "2013-11-25" @default.
• W1591939718 modified "2023-09-25" @default.
• W1591939718 title "Power Estimates for Voxel-Based Genetic Association Studies Using Diffusion Imaging" @default.
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• W1591939718 doi "https://doi.org/10.1007/978-3-319-02475-2_21" @default.
• W1591939718 hasPublicationYear "2013" @default.
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