Metadata-Version: 1.0
Name: helixpc
Version: 1.0.0
Summary: Automisation of graph generation for gene FC databases.
Home-page: https://github.com/Cathaspa/HelixPC
Author: Anne-Laure Ehresmann
Author-email: cathaspa@protonmail.com
License: MIT
Description: ========
        HelixPC
        ========
        
        A series of scripts for gene database automation. Developed for the
        Philippe Campeau Laboratory.
        
        
        .. image:: http://i.imgur.com/pRZoaiC.png
          :width: 800px
          :align: center
          :alt: alternate text
        
        
        Installation
        ------------
        
        Dependencies
        ^^^^^^^^^^^^
        * pandas 
        * numpy 
        * plotly
        
        
        Clone the repository, and install the dependencies. Looking into
        `pip <https://pypi.python.org/pypi/pip>`_ will make installing the
        python packages notably easier.
        
        Once finished, you can call the script with::
        
          $ python helixpc.py [options] 
            
        Usage
        -----
        
        Generating a file for the graphing utility
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        ::
         
        $ helixpc.py group <group_input> [--nonan]
        
        If you do not yet have a valid input file for graph generation, the
        command ``group`` can help you generate one automatically. Simply stick
        all your batches in a single csv file, call the utility and a file
        named ``output.csv`` will be generated. You can then feed to the
        graphing utility.
        
        input file format: 
        """"""""""""""""""
        
        - Check the example ``group_input.csv``
        - The first row should specify the column titles.  
        - You *must* call the columns containing gene names ``gene_symbol``, 
          they are used as columns of reference by the scripts.
        
        note that: 
        
        - If certain genes are included multiple times, their
          mean will be calculated, and only a single entry will appear in 
          the output.
         
        - you may pass ``[--nonan]`` or ``[-n]`` to omit any gene that
          are missing entries in a batch.  
        
        Using the graphing utility
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
        ::
        
        $ helixpc.py graph <graph_input> [--heat] [--scatter] <control> <sample> [<sample> ...]
        
        Once you have a csv file that you want to use for generating graph,
        you may feed it to the graphing utility.  You must give the csv file a
        series of arguments for it to function properly:
        
        ``--scatter``
        
        Specifies that you want scatter graph(s).  Scatter graphs are
        generated with a control (always the same) in the x axis, and a sample
        in the y axis. Giving more than one sample will return to you multiple
        graphs, one for each sample. You can hover over each point to see the
        name of the gene it is representing.
        
        ``--heat``
        
        Specifies that you want a heat graph.  Not implemented yet.
        
        ``<control>``
        
        Specifies the control. You may give an index or the name of a
        column. You may also give a series of indexes/column-names separated
        by a comma, and the values used will be the mean of each row for the
        series of columns given.
        
        ``<sample>``
        
        Specifies the first sample. You may give an index or the name of a
        column. You may also give a series of indexes/column-names separated
        by a comma, and the values used will be the mean of each row for the
        series of columns given.
        
        ``[<sample> ...]``
        
        indicates that you can give more than one sample, simply separate each
        sample with a space.
        
        input file format:
        """"""""""""""""""
        
        - Check the example ``graph_input.csv`` The first row should specify
          the column titles.
        - The first col should contain ``gene_symbol`` 
        
Platform: UNKNOWN
