ez.combat: Easy ComBat Harmonization

A dataframe-friendly implementation of ComBat Harmonization which uses an empirical Bayesian framework to remove batch effects. Johnson WE & Li C (2007) <doi:10.1093/biostatistics/kxj037> "Adjusting batch effects in microarray expression data using empirical Bayes methods." Fortin J-P, Cullen N, Sheline YI, Taylor WD, Aselcioglu I, Cook PA, Adams P, Cooper C, Fava M, McGrath PJ, McInnes M, Phillips ML, Trivedi MH, Weissman MM, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.11.024> "Harmonization of cortical thickness measurements across scanners and sites." Fortin J-P, Parker D, Tun<e7> B, Watanabe T, Elliott MA, Ruparel K, Roalf DR, Satterthwaite TD, Gur RC, Gur RE, Schultz RT, Verma R, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.08.047> "Harmonization of multi-site diffusion tensor imaging data."

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: stats
Published: 2021-06-07
Author: Timothy R. Koscik [aut, cre, cph]
Maintainer: Timothy Koscik <timothy-koscik at uiowa.edu>
License: Artistic-2.0
NeedsCompilation: no
Materials: README
CRAN checks: ez.combat results


Reference manual: ez.combat.pdf


Package source: ez.combat_1.0.0.tar.gz
Windows binaries: r-devel: ez.combat_1.0.0.zip, r-release: ez.combat_1.0.0.zip, r-oldrel: ez.combat_1.0.0.zip
macOS binaries: r-release (arm64): ez.combat_1.0.0.tgz, r-oldrel (arm64): ez.combat_1.0.0.tgz, r-release (x86_64): ez.combat_1.0.0.tgz


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