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fMRIscrub: Scrubbing and Other Data Cleaning Routines for fMRI

Data-driven fMRI denoising with projection scrubbing (Pham et al (2022) <doi:10.1016/j.neuroimage.2023.119972>). Also includes routines for DVARS (Derivatives VARianceS) (Afyouni and Nichols (2018) <doi:10.1016/j.neuroimage.2017.12.098>), motion scrubbing (Power et al (2012) <doi:10.1016/j.neuroimage.2011.10.018>), aCompCor (anatomical Components Correction) (Muschelli et al (2014) <doi:10.1016/j.neuroimage.2014.03.028>), detrending, and nuisance regression. Projection scrubbing is also applicable to other outlier detection tasks involving high-dimensional data.

Version:	0.14.5
Depends:	R (≥ 3.5.0)
Imports:	MASS,cellWise,e1071,fMRItools (≥ 0.2.2),pesel,robustbase, stats,expm, utils,gamlss
Suggests:	corpcor,cowplot,ciftiTools,gifti,knitr,rmarkdown,RNifti,ggplot2,fastICA,oro.nifti,testthat (≥ 3.0.0),covr
Published:	2023-10-25
DOI:	10.32614/CRAN.package.fMRIscrub
Author:	Amanda Mejia [aut, cre], John Muschelli [aut], Damon Pham [aut], Daniel McDonald [ctb], Fatma Parlak [ctb]
Maintainer:	Amanda Mejia <mandy.mejia at gmail.com>
BugReports:	https://github.com/mandymejia/fMRIscrub/issues
License:	GPL-3
URL:	https://github.com/mandymejia/fMRIscrub
NeedsCompilation:	no
Citation:	fMRIscrub citation info
Materials:	README,NEWS
CRAN checks:	fMRIscrub results

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