pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods
pyComBat  is a Python 3 implementation of ComBat , one of the most widely used tool for correcting technical biases, called batch effects, in microarray expression data.
More detailed documentation can be found at this address.
We list here the versions of the packages that have been used for development/testing of pyComBat, as well as for writing the documentation.
- sphinx 2.1.2
You can install pyComBat directly with:
pip install combat
You can upgrade pyComBat to its latest version with:
pip install combat --upgrade
The simplest way of using pyComBat is to first import it, and then simply use the pycombat function with default parameters:
from combat.pycombat import pycombat data_corrected = pycombat(data,batch)
data: The expression matrix as a dataframe. It contains the information about the gene expression (rows) for each sample (columns).
batch: List of batch indexes. The batch list describes the batch for each sample. The list of batches contains as many elements as the number of columns in the expression matrix.
How to contribute
Please refer to CONTRIBUTING.md to learn more about the contribution guidelines.
 Behdenna A, Haziza J, Azencot CA and Nordor A. (2020) pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods. bioRxiv doi: 10.1101/2020.03.17.995431
 Johnson W E, et al. (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics, 8, 118–127
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