ModelArray: An R package for statistical analysis of fixel-wise data

• DOI: 10.1016/j.neuroimage.2023.120037
• Publication Date: 2023-03-15T16:49:16Z
• Authors: Chenying Zhao; Tinashe M. Tapera; Joëlle Bagautdinova; Josiane Bourque; Sydney Covitz; Raquel E. Gur; Ruben C. Gur; Bart Larsen; Kahini Mehta; Steven L. Meisler; Kristin Murtha; John Muschelli; David R. Roalf; Valerie J. Sydnor; Alessandra M. Val...; Russell T. Shinohara; Matthew Cieslak; Theodore D. Satte...
• Keywords: Univariate; Computational statistics; R package; Profiling (computer programming); Statistical Analysis; Data Analysis

Diffusion MRI is the dominant non-invasive imaging method used to characterize white matter organization in health and disease. Increasingly, fiber-specific properties within a voxel are analyzed using fixels. While tools for conducting statistical analyses of fixel-wise data exist, currently available support only limited number models. Here we introduce ModelArray, an R package mass-univariate analysis data. At present, ModelArray supports linear models as well generalized additive (GAMs), which particularly useful studying nonlinear effects lifespan In addition, also aims scalable analysis. With several lines code, even large datasets can be standard personal computer. Detailed memory profiling revealed that required datasets. As example, applied derived from diffusion images acquired part Philadelphia Neurodevelopmental Cohort (n = 938). anticipated developmental matter. Moving forward, supported by open-source software development model incorporate additional other types. Taken together, provides flexible efficient platform