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"description": "Probabilistic 20/20\n===================\n\nThe Probabibilistic 20/20 test identifies genes with signficant oncogene-like and tumor suppressor gene-like mutational patterns for small coding region variants. \nPutative signficant oncogenes are found through evaluating \nmissense mutation clustering and *in silico* pathogenicity scores. Often highly clustered missense\nmutations are indicative of activating mutations.\nWhile statistically signficant tumor suppressor genes (TSGs) are found by abnormally high proportion of inactivating mutations.\n\nProbabilistic 20/20 evaluates statistical significance by employing \nmonte carlo simulations, which incorporates observed mutation context. Monte carlo\nsimulations are performed within the same gene and thus avoid building a background\ndistribution based on other genes. This means that the statistical test can be applied \nto either all genes in the exome from exome sequencing or to a certain target set of genes\nfrom targeted sequencing.\n\nThe Probabilistic 20/20 test has nice properties since it accounts\nfor several factors that could effect the significance of driver genes.\n\n* gene length\n* mutation context\n* gene sequence (e.g. codon bias)\n\nDocumentation\n-------------\n\n.. image:: http://readthedocs.org/projects/probabilistic2020/badge/?version=latest\n :target: http://probabilistic2020.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\nPlease see the `documentation `_ on readthedocs for more details.\n\nCitation\n--------\n\nCollin J. Tokheim, Nickolas Papadopoulos, Kenneth W. Kinzler, Bert Vogelstein, and Rachel Karchin. Evaluating the evaluation of cancer driver genes. PNAS 2016 ; published ahead of print November 22, 2016, doi:10.1073/pnas.1616440113\n\nIf you use the hotmaps1d command to find codons were missense mutations are significantly clustered, please cite the HotMAPS paper:\n\nTokheim C, Bhattacharya R, Niknafs N, Gygax DM, Kim R, Ryan M, Masica DL, Karchin R (2016) Exome-scale discovery of hotspot mutation regions in human cancer using 3D protein structure Cancer Research. Apr. 28.pii: canres.3190.2015. \n\nInstallation\n------------\n\n.. image:: https://travis-ci.org/KarchinLab/probabilistic2020.svg?branch=master\n :target: https://travis-ci.org/KarchinLab/probabilistic2020\n\n\nPython Package Installation\n~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nUsing the python package installation, all the required python packages for the probabibilistic 20/20 test will automatically be installed for you.\n\nTo install the package into python you can use `pip`. If you are installing to a system wide python then you may need to use `sudo` before the pip command.\n\n.. code-block:: bash\n\n $ pip install probabilistic2020\n\nThe scripts for Probabilstic 20/20 can then be found in `Your_Python_Root_Dir/bin`. You can\ncheck the installation with the following:\n\n.. code-block:: bash\n\n $ which probabilistic2020\n $ probabilistic2020 --help\n\nLocal installation\n~~~~~~~~~~~~~~~~~~\n\nLocal installation is a good option if you do not have privilege to install a python package and already have the required packages. The source files can also be manually downloaded from github at https://github.com/KarchinLab/probabilistic2020/releases.\n\n**Required packages:**\n\n* numpy\n* scipy\n* pandas>=0.17.0\n* pysam\n\nIf you don't have the above required packages, you will need to install them. For the following commands to work you will need `pip `_. If you are using a system wide python, you will need to use `sudo` before the pip command. Also if you are using python 3.X then you likely will have to install pysam version >=0.9.0.\n\n.. code-block:: bash\n\n $ cd probabilistic2020\n $ pip install -r requirements.txt\n\nIf you want the exact package version used for development on python 2.7, then instead use the requirements_dev.txt. Next you will need to build the Probabilistic 20/20 source files. This is can be accomplished in one command.\n\n.. code-block:: bash\n\n $ make build\n\nOnce finished building you can then use the scripts in the `probabilstic2020/prob2020/console` directory. You can check the build worked by the following:\n\n.. code-block:: bash\n\n $ python prob2020/cosole/probabilistic2020.py --help",
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