Metadata-Version: 1.1
Name: presto
Version: 0.5.1
Summary: A bioinformatics toolkit for processing high-throughput lymphocyte receptor sequencing data.
Home-page: http://clip.med.yale.edu/presto
Author: Jason Anthony Vander Heiden
Author-email: jason.vanderheiden@yale.edu
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Description: Version 0.5.1: December 4, 2015
        ===============================
        
        pRESTO is a toolkit for processing raw reads from high-throughput
        sequencing of lymphocyte repertoires. Dramatic improvements in
        high-throughput sequencing technologies now enable large-scale
        characterization of immunoglobulin repertoires, defined as the
        collection of trans-membrane antigen-receptor proteins located on the
        surface of T and B lymphocytes. The REpertoire Sequencing TOolkit
        (pRESTO) is composed of a suite of utilities to handle all stages of
        sequence processing prior to germline segment assignment. pRESTO is
        designed to handle either single reads or paired-end reads. It includes
        features for quality control, primer masking, annotation of reads with
        sequence embedded barcodes, generation of single-molecule consensus
        sequences, assembly of paired-end reads and identification of duplicate
        sequences. Numerous options for sequence sorting, sampling and
        conversion operations are also included.
        
        Requirements
        ------------
        
        -  `Python 3.4.0 <http://python.org>`__
        -  `setuptools 2.0 <http://bitbucket.org/pypa/setuptools>`__
        -  `NumPy 1.8 <http://numpy.org>`__
        -  `SciPy 0.14 <http://scipy.org>`__
        -  `pandas 0.15 <http://pandas.pydata.org>`__
        -  `Biopython 1.65 <http://biopython.org>`__
        -  `MUSCLE v3.8 <http://www.drive5.com/muscle>`__
        -  `USEARCH v7.0 <http://www.drive5.com/usearch>`__
        
        Installation - Linux
        --------------------
        
        1. The simplest way to install all Python dependencies is to install the
           full SciPy stack using the
           `instructions <http://scipy.org/install.html>`__, then install
           Biopython according to its
           `instructions <http://biopython.org/DIST/docs/install/Installation.html>`__.
        
        2. | Extract the pRESTO bundle and run:
           |  ``> python3 setup.py install --user``
        
        Installation - Windows
        ----------------------
        
        1. Install Python 3.4.0+ from `Python <http://python.org/downloads>`__,
           selecting both the options 'pip' and 'Add python.exe to Path'.
        
        2. Install NumPy, SciPy, pandas and Biopython using the packages
           available from the `Unofficial Windows
           binary <http://www.lfd.uci.edu/~gohlke/pythonlibs>`__ collection.
        
        3. | Unzip the pRESTO bundle, open a Command Prompt, change directories
             to the pRESTO folder, and run:
           |  ``> python setup.py install``.
        
        4. For a default installation of Python 3.4, the pRESTO scripts will be
           installed into ``C:\Python34\Scripts`` and should be directly
           executable from the Command Prompt. If this is not the case, then
           follow step 5 below.
        
        5. Add both the ``C:\Python34`` and ``C:\Python34\Scripts`` directories
           to your ``%Path%``. On Windows 7 the ``%Path%`` setting is located
           under Control Panel -> System and Security -> System -> Advanced
           System Settings -> Environment variables -> System variables -> Path.
        
        Installation - Mac OS X
        -----------------------
        
        1. Install Xcode 3.2.6 Available from the Apple store or `developer
           downloads <http://developer.apple.com/downloads>`__. If you have a
           newer version (eg, Xcode 4.6.3) that will work also, but Xcode 3 is
           free of charge. If Xcode fails to install with an "Unknown Error",
           change the date on your system to some time in 2011, install Xcode,
           and then change the date back to the proper setting.
        
        2. Install XQuartz 2.7.5 Available from the `XQuartz
           project <http://xquartz.macosforge.org/landing>`__.
        
        3. Install Homebrew Follow the installation and post-installation
           `instructions <http://brew.sh>`__.
        
        4. | Open a terminal and install gfortran (required for SciPy) using
             Homebrew (this can take an hour to install):
           |  ``> brew install gfortran``
           |  If the above fails run this instead:
           |  ``> brew install --env=std gfortran``
        
        5. | Install Python 3.4.0+ and set the path to the python3 executable:
           |  ``> brew install python3``
           |  ``> echo 'export PATH=/usr/local/bin:$PATH' >> ~/.profile``
           |  Exit and reopen the terminal application so the PATH setting takes
             effect
        
        6. | Install NumPy, SciPy, pandas and Biopyton using the Python package
             manager:
           |  ``> pip3 install numpy scipy pandas biopython``
        
        7. | Extract the pRESTO bundle, open a terminal window, change
             directories to the pRESTO folder, and run:
           |  ``> python3 setup.py install``
        
Keywords: bioinformatics immunoglobulin lymphocyte sequencing
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
