cmapPy 1.0.5

Assorted tools for interacting with .gct, .gctx files and other Connectivity Map (Broad Institute) data/tools

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**cmapPy:** Tools for interacting with .gctx and .gct files, and other Connectivity Map resources
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
**Connectivity Map, Broad Institute of MIT and Harvard**

`<http://cmappy.readthedocs.io/en/latest/>`_

For more information on the file formats and available resources, please see `clue.io/gctx <https://clue.io/gctx>`_.

Maintainer
==========

Oana Enache

[e-mail]

Requirements
======================

As of April 11th, 2017, cmapPy has the following dependencies:

- **Python 2.7** (specifically, we use 2.7.11)
- h5py==2.6.0
- numpy==1.11.2
- pandas==0.18
- requests==2.13.0

Note that more recent versions of these packages should also work (except for Python3), should you choose to use them; however, we cannot guarantee package behavior for more recent packages. For contributors (see "Contributing" for further details), we request that you develop and submit any pull requests using the above environment.

Installation and setup
======================

We recommend the use of cmapPy with a virtual environment (here we demonstrate how to use it with conda).

**Option 1 (recommended): Setup pandasGEXpress in a new conda environment**

* (If you haven't already) install ``miniconda``
* Download/follow instructions provided `here <https://conda.io/miniconda.html>`_. Unless you have personal preferences/reasons to do so, we recommend installing Miniconda over Anaconda because it's more lightweight.
* On the command line, type ``conda info`` to verify that conda has been properly instaled on your system. You should see some information about the "current conda install"; if not, your installation didn't work.
* Create your cmapPy environment: ``conda create --name my_cmapPy_env python=2.7.11 numpy=1.11.2 pandas=0.18 h5py=2.6.0 requests==2.13.0``
* Activate your cmapPy environment: ``source activate my_cmapPy_env``
* **In your activated conda environment**, pip install cmapPy: ``pip install cmapPy``

**Option 2: Install cmapPy from PyPI**

* ``pip install cmapPy``
* Note: For use of other virtualenvs, we include a requirements.txt file in the cmapPy package that you can use to install the proper versions of depencies.


Subpackages included
====================

* **pandasGEXpress**: Parsers, writers, and utility methods for .gctx and .gct files. Integrated with `pandas <http://pandas.pydata.org/>`_, enabling easy access to popular and powerful Python data science tools for analysis pipelines.

* **cmap_api_client**: A Python API client for accessing and retrieving information from the `Connectivity Map API <https://clue.io/api>`_

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1) pandasGEXpress
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Contents Overview
"""""""""""""""""
pandasGEXpress represents .gctx and .gct files as instances of a GCToo object; in essence, this is a class that contains and maintains requirements between separate pandas DataFrames of the files' expression data, row metadata, and column metadata and some file attributes (source, version). More details on `clue.io/gctx <https://clue.io/gctx>`_. **Note that we currently only support GCTX version 1.0 and GCT versions 1.2 and 1.3**.

* ``GCToo.py``: main class for storing contents of .gctx, .gct files.
* ``concat_gctoo.py``: Concatenate (horizontally or vertically) two or more GCToo instances in a Python session or two {.gct, .gctx} files from the command line.
* ``gct2gctx.py``: Command line tool to convert a .gct file to .gctx.
* ``gct2gctx.py``: Command line tool to convert a .gctx file to a .gct
* ``parse.py``: Parse in .gct, .gctx files to a new GCToo instance
* ``plate_grp.py``: Read and write .grp files to a list.
* ``random_slice.py``: Slices a random subset of a GCToo file to a specified size.
* ``slice_gct.py``: Slice a GCToo instance by including/excluding a list of row ids, column ids, row indexes, column indexes, or a combination thereof.
* ``write_gct.py``: Write a .gct file from a GCToo instance.
* ``write_gctx.py``: Write a .gctx file from a GCToo instance.
A suite of unit tests is also included in the ``/tests`` directory. Sample files for testing can be found in ``/tests/functional_tests``.

Tutorials and example use
"""""""""""""""""""""""""
We recommend referencing our Tutorial section on `clue.io/gctx <https://clue.io/gctx>`_ to see further demonstrations on how one might use a combination of cmapPy and pandas methods for common data analysis and manipulation tasks.

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2) cmap_api_client
***************

clue_api_client is a simple class that can be used to query the CLUE API.

Contents Overview
"""""""""""""""""
* ``cell_queries.py``: Methods for cell line-related queries.
* ``clue_api_client.py``: Main class representing a client, for running queries against the CLUE API.
* ``gene_queries.py``: Methods for gene-related queries.
* ``macchiato_queries.py``: Methods for brew_prefix related queries.
* ``mock_clue_api_client.py``: Mock API for testing.
* ``pert_queries.py``: Methods for perturbagen-related queries.

Tutorials and example use
"""""""""""""""""""""""""

Coming soon!

Contributing
====================

We welcome contributors! For your pull requests, please include the following:

* Sample code/file that reproducibly causes the bug/issue
* Documented code providing fix
* Unit tests evaluating added/modified methods.