fMRIscrub: Scrubbing and Other Data Cleaning Routines for fMRI
Data-driven fMRI denoising with projection scrubbing (Pham et al
(2022) <arXiv:2108.00319>). 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 and DVARS are also applicable to other
outlier detection tasks involving high-dimensional data.
Version: |
0.11.2 |
Depends: |
R (≥ 3.5.0) |
Imports: |
MASS, e1071, pesel, robustbase, stats, utils |
Suggests: |
corpcor, cowplot, ciftiTools, gifti, knitr, rmarkdown, RNifti, ggplot2, gsignal, fastICA, oro.nifti, testthat (≥
3.0.0), covr |
Published: |
2022-07-08 |
Author: |
Amanda Mejia [aut, cre],
John Muschelli
[aut],
Damon Pham [aut],
Daniel McDonald [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 |
Documentation:
Downloads:
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