Metadata-Version: 2.1
Name: pyComBat-test
Version: 0.1.2
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/).
        
        ## 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:
        
        ```python
        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](https://github.com/epigenelabs/pyComBat/blob/master/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
        
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
