Metadata-Version: 2.1
Name: combat
Version: 0.3.0
Summary: pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods
Home-page: https://github.com/epigenelabs/pyComBat
Author: Abdelkader Behdenna
Author-email: abdelkader@epigenelabs.com
License: UNKNOWN
Description: # 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](https://epigenelabs.github.io/pyComBat/).
        
        ## TO DO
        
        ## Minimum dependencies
        
        We list here the versions of the packages 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
        
        * patsy 0.5.1
        
        ### Documentation
        
        * sphinx 2.1.2
        
        ## Usage example
        
        ### Installation
        
        You can install pyComBat directly with:
        
        ```python
        pip install combat
        ```
        
        You can upgrade pyComBat to its latest version with:
        
        ```python
        pip install combat --upgrade
        ```
        
        ### Running pyComBat
        
        The simplest way of using pyComBat is to first import it, and then simply use the pycombat function with default parameters:
        
        ```python
        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](https://github.com/epigenelabs/pyComBat/blob/master/CONTRIBUTING.md) to learn more about the contribution guidelines.
        
        ## References
        
        [1] 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
        
        [2] Johnson W E, et al. (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics, 8, 118–127
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
