Binaries
========

Overview
--------

Precompiled or prepackaged versions of OpenMS, PyProphet and msproteomicstools
are readily available for most supported platforms. 

OpenMS
------
OpenSWATH is completely integrated into `OpenMS <http://www.openms.org>`_. The
current releases can be obtained from `GitHub
<https://github.com/OpenMS/OpenMS/releases>`_. To make use of the latest
developments, consider using the `nightly builds for Windows and macOS
<https://abibuilder.informatik.uni-tuebingen.de/archive/openms/OpenMSInstaller/nightly/>`_.

Instructions for compilation and installation can be obtained from the `OpenMS
documentation
<http://ftp.mi.fu-berlin.de/pub/OpenMS/release-documentation/html/index.html>`_.

EasyPQP
-------

EasyPQP requires Python 3. Windows users should install
Anaconda. Mac and Linux users should be able to install PyProphet directly from
GitHub. It is strongly recommended to install PyProphet within a `virtualenv
<https://virtualenv.pypa.io/en/stable/userguide/>`_.

.. code-block:: bash
   
   # Install PyProphet release version
   pip install easypqp

   # Alternative: Install PyProphet development version
   pip install git+https://github.com/grosenberger/easypqp.git@master

PyProphet
---------

PyProphet requires Python 2.7 or Python 3. Windows users should install
Anaconda. Mac and Linux users should be able to install PyProphet directly from
GitHub. It is strongly recommended to install PyProphet within a `virtualenv
<https://virtualenv.pypa.io/en/stable/userguide/>`_.

.. code-block:: bash

   # Install dependencies
   pip install numpy scipy scikit-learn pandas numexpr statsmodels Click matplotlib seaborn
   
   # Install PyProphet release version
   pip install pyprophet

   # Alternative: Install PyProphet development version
   pip install git+https://github.com/PyProphet/pyprophet.git@master


msproteomicstools & TRIC
------------------------
msproteomicstools requires Python 2.7 and can be installed through ``pip``. On
Microsoft Windows you will first have to install Python (the easiest way to do
this is to download `Anaconda <https://www.continuum.io/anaconda-overview>`_).
You can then install msproteomicstools through `PyPI
<https://pypi.python.org/pypi/msproteomicstools>`_:

.. code-block:: bash

   pip install numpy
   pip install msproteomicstools

You can alternatively download the msproteomicstools release directly from PyPI.
To obtain the latest development version, please download the code from `GitHub
<https://github.com/msproteomicstools/msproteomicstools>`_. If you are using
Microsoft Windows and Anaconda, it is possible that BioPython does not properly
install and you may have to install it through Anaconda:

.. code-block:: bash

   conda install biopython

DIAlignR
--------

DIAlignR is an R package and can be installed through BioConductor and requires R >= 4.0. 

.. code-block:: r

   if(!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
   BiocManager::install("DIAlignR")

ARYCAL
------

ARYCAL is a standalone tool written in rust and can be download from the `GitHub repo release page <https://github.com/singjc/arycal/releases>`_.

MOBI-DIK & diapysef
-------------------
MOBI-DIK uses a python package ``diapysef`` for data conversion and library
generation. It requires Python 3 and can be installed through ``pip``. For
analyzing ion mobility data, a Bruker distributed sdk library is required. The
sdk library can be obtained through Bruker distributions or through installing
`ProteoWizard <http://proteowizard.sourceforge.net/download.html>`_. The
libraries would be ``timsdata.dll`` for Windows and ``libtimsdata.so`` for
Linux. You can install diapysef through `PyPI
<https://pypi.org/project/diapysef/>`_:

.. code-block:: bash

   pip install diapysef