Install

Requirements

Hardware

  • CPU
    • Quad Core 2.5GHz or better
      • More cores = faster run time when running multiple samples
      • Faster GHz = faster each sample runs
  • RAM
    • At least 1GB per CPU core for small genomes(Dengue, Flu,...)

Python Packages

All python packages can be defined in a pip requirements.txt file The pipeline comes with all of the necessary python packages already defined inside of requirements.txt.

System Packages

The pipeline requires some system level packages(software installed via your Linux distribution’s package manager) The installer looks for the system_packages.lst and installs the correct packages using that file. This file is a simple json formatted file that defines packages for each package manager

Roche Utilities

If you intend on using the roche_sync you will need to ensure that the sfffile command is in your PATH. That is, if you execute $> sfffile it returns the help message for the command.

This command should automatically be installed and put in your path if you install the Data Analysis CD #3 that was given to you with your Roche instrument.

MidParse.conf

If you inted on using the roche_sync you may need to edit the included ngs_mapper/MidParse.conf file before installing. This file is formatted to be used by the Roche utilities and more information about how it is used can be found in the Roche documentation.

Installation

  1. Clone

    Assumes you already have git installed. If not you will need to get it installed by your system administrator.

    git clone https://githubusername@github.com/VDBWRAIR/ngs_mapper.git
cd ngs_mapper

  1. Install System Packages

    This is the only part of the installation process that you should need to become the super user

    • Red Hat/CentOS(Requires the root password)

      su -c 'python setup.py install_system_packages && chmod 666 -R setuptools*'

    • Ubuntu

      sudo python setup.py install_system_packages && sudo chmod 666 -R setuptools*

  2. Configure the defaults

    You need to configure the ngs_mapper/config.yaml file.

    1. Copy the default config to config.yaml

      cp ngs_mapper/config.yaml.default ngs_mapper/config.yaml

    2. Then edit the ngs_mapper/config.yaml file which is in yaml format

      The most important thing is that you edit the NGSDATA value so that it contains the path to your NGSDATA directory.

      The path you use for NGSDATA must already exist

      mkdir -p /path/to/NGSDATA

  3. Python

    The ngs_mapper requires python 2.7.3+ but < 3.0

    • Ensure python is installed

      python setup.py install_python

    • Quick verify that Python is installed

      The following should return python 2.7.x(where x is somewhere from 3 to 9)

      $HOME/bin/python --version

  4. Setup virtualenv

    1. Where do you want the pipeline to install? Don’t forget this path, you will need it every time you want to activate the pipeline

      venvpath=$HOME/.ngs_mapper

    2. Install the virtualenv to the path you specified

      wget --no-check-certificate https://pypi.python.org/packages/source/v/virtualenv/virtualenv-1.11.6.tar.gz#md5=f61cdd983d2c4e6aeabb70b1060d6f49 -O- | tar xzf -
$HOME/bin/python virtualenv-1.11.6/virtualenv.py --prompt="(ngs_mapper) " $venvpath

    1. Activate the virtualenv. You need to do this any time you want to start using the pipeline

      . $HOME/.ngs_mapper/bin/activate

  5. Install the pipeline into virtualenv

    python setup.py install

    It should be safe to run this more than once in case some dependencies do not fully install.

Build and view complete documentation

cd doc
make clean && make html
firefox build/html/install.html#build-and-view-complete-documentation
cd ..

Verify install

You can pseudo test the installation of the pipeline by running the functional tests

nosetests ngs_mapper/tests/test_functional.py