pyComBat-test 0.1.2

pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods

pyComBat

pyComBat [1] is a Python 3 implementation of ComBat [2], 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.

Minimum dependencies

We list here the versions of the paquages that have been used for development/testing of pyComBat, as well as for writing the documentation.

pyCombat dependencies

• python 3.6

• numpy 1.16.4

• mpmath 1.1.0

• pandas 0.24.2

Documentation

• sphinx 2.1.2

Usage example

Note that you need to download the utils.py script and put it in the same folder as the rest of your code. We are currently working on making on making pyComBat usable as a Python library.

The simplest way of using pyComBat is to first import it, and simply use the pycombat function with default parameters:

from utils import pycombat
pycombat(data,batch)

• data: The expression matrix. It contains the information about the gene expression (rows) for each sample (columns). The first column (resp. row) is dedicated for the gene (resp. sample) names.

• 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.

References

[1]

[2] Johnson,W.E. et al. (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics, 8, 118–127