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) "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) "Harmonization of cortical thickness measurements across scanners and sites." Fortin J-P, Parker D, Tun B, Watanabe T, Elliott MA, Ruparel K, Roalf DR, Satterthwaite TD, Gur RC, Gur RE, Schultz RT, Verma R, & Shinohara RT (2017) "Harmonization of multi-site diffusion tensor imaging data."

ComBat Harmonization for multi-site/batch data with Dataframe Objects

Version 1.0.0

Maintainer: Timothy R. Koscik, [email protected]
License: Artistic License 2.0

This is a modification of the ComBat function code from the sva package that can be found at:
Standard Version: https://bioconductor.org/packages/release/bioc/html/sva.html
Prior Modified Version: https://github.com/Jfortin1/ComBatHarmonization

Current Modifications:
The standard version has been modified to add an interface to standard R dataframes as input.

• In the standard version, input data must be a p x n matrix, with p features in rows and n participants in columns, while in the modified version, input data can be n x p dataframes, with p features in columns and n participants in rows.
• The modified version adds procedures to allow batch variables to be within the same dataframe as the data as well as methods to select and exclude subsets of features (columns) in dataframes.
• Various formatting changes to the standard version source code have been mode.

References: If you are using ComBat for the harmonization of multi-site imaging data, please cite the following papers: