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combat.enigma (version 1.1)

Fit and Apply ComBat, LMM, or Prescaling Harmonization for ENIGMA and Other Multisite MRI Data

Description

Fit and apply ComBat, linear mixed-effects models (LMM), or prescaling to harmonize magnetic resonance imaging (MRI) data from different sites. Briefly, these methods remove differences between sites due to using different scanning devices, and LMM additionally tests linear hypotheses. As detailed in the manual, the original ComBat function was first modified for the harmonization of MRI data (Fortin et al. (2017) ) and then modified again to create separate functions for fitting and applying the harmonization and allow missing values and constant rows for its use within the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium (Radua et al. (2020) ); this package includes the latter version. LMM calls "lme" massively considering specific brain imaging details. Finally, prescaling is a good option for fMRI, where different devices can have varying units of measurement.

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Version

Install

install.packages('combat.enigma')

Monthly Downloads

507

Version

1.1

License

Artistic License 2.0

Maintainer

Joaquim Radua

Last Published

October 17th, 2024

Functions in combat.enigma (1.1)

prescale_fit

Fit and apply brain imaging prescaling
combat_example

Simulated MRI data for combat_fit/apply
lmm_fit

Fit LMM harmonization and obtain model coefficients
combat_fit

Fit and apply ComBat harmonization