Package: combat.enigma 1.1.1

combat.enigma: Fit and Apply ComBat, LMM, or Prescaling Harmonization for ENIGMA and Other Multisite MRI Data

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) <doi:10.1016/j.neuroimage.2017.11.024>) 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) <doi:10.1016/j.neuroimage.2020.116956>); 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.

Authors:Joaquim Radua [aut, cre]

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combat.enigma.pdf |combat.enigma.html
combat.enigma/json (API)
NEWS

# Install 'combat.enigma' in R:
install.packages('combat.enigma', repos = c('https://jrad1.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 645 downloads 5 exports 104 dependencies

Last updated from:4e014832aa. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK168
source / vignettesOK212
linux-release-x86_64OK190
macos-release-arm64OK215
macos-oldrel-arm64OK167
windows-develOK156
windows-releaseOK125
windows-oldrelOK131
wasm-releaseOK128

Exports:combat_applycombat_fitlmm_fitprescale_applyprescale_fit

Dependencies:abindbackportsbootbroomcarcarDatacaretclasscliclockcodetoolscolorspacecowplotcpp11data.tableDerivdiagramdigestdoBydplyre1071farverforeachforecastFormulafracdifffuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlme4lmtestlubridatemagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqaModelMetricsmodelrnlmenloptrnnetnumDerivparallellypbkrtestpillarpkgconfigplyrpROCprodlimprogressrproxypurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackrecipesreformulasreshape2rlangrpartS7scalesshapeSparseMsparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdburcautf8vctrsviridisLitewithrzoo