Package: pastaq
InstallationTo install from source, you will need to install a suitable C++ compiler and
corresponding build tools for your platform as well as CMake and zlib.
The instructions listed here refer to the installation of PASTAQ's Python
bindings.  Currently the only external dependencies other than zlib are included
as git submodules.To get started, clone this repository and initialize git submodules:git clone https://github.com/PASTAQ-MS/PASTAQ.git
cd PASTAQ
git submodule init
git submodule updateAs usual, it is strongly recommended to create a Python environment in which to build Pastaq, and the core development has been with Python 3.7.8, but other versions may be fine.Special build instructions for WindowsWindows requires a static version of zlib, and the one recommended iszlib-win-build.
The core Windows work with Pastaq has been with Visual studio 2017, so it is recommended for building zlib and Pastaq.  Once you have built zlib, you must pointCMakeLists.txtto the include directory and library according to the commented example at the top of that file.When building Pastaq in Windows, first open a Visual Studio command prompt using Tools->Visual Studio Command Prompt in the Visual Studio IDE so that you have access to the compiler and linker.  Then, in that command window, activate your Pastaq Python environment and proceed with the instructions below.Build the module and install it in your system:# Installationpython3setup.pyinstall--user# Developmentpython3setup.pydevelop--userNow it can be imported and used in python as follows:importpastaqraw_data=pastaq.read_mzxml(...)UsageExamples of the usage of the PASTAQ can be found in theexamplesfolder. To
run them, install pastaq as previously described, update the input path of the
mzXML and mzID files, change any necessary parameters and run it with:python examples/small_range.pyYou can use any mzXML files and identifications in mzIdentML v1.1+. If no
identifications are available, remove theident_pathfrom the input files
array or set it to'none'. You can find the files we used for testing and
development via ProteomeXchange, with identifierPXD024584.Processing of mzML files is in an early stage and may lead to some issues.For more information about PASTAQ and the configuration of the parameters,
please visitthe official website.Compile the pastaq library from sourceFor an out of source build of the library, create a build directory and run cmake:mkdirbuildcdbuild
cmake..
makeIf you wish to enable the compilation of the tests you need to set up thePASTAQ_ENABLE_TESTSflag to 1. A limited number of automated test are
currently available but we are looking forward to improve this in the future.mkdirbuildcdbuild
cmake..-DPASTAQ_ENABLE_TESTS=1make
maketestAdditionally, you can use the Ninja building tool for faster compilation times.mkdirbuildcdbuild
cmake..-DPASTAQ_ENABLE_TESTS=1-GNinja
ninja
ninjatestHow to cite this workThe main manuscript has been published in as Open Access Analytical Chemistry with the following details:Alejandro Sánchez Brotons, Jonatan O. Eriksson, Marcel Kwiatkowski, Justina C. Wolters, Ido P. Kema, Andrei Barcaru, Folkert Kuipers, Stephan J. L. Bakker, Rainer Bischoff, Frank Suits, and Péter Horvatovich, Pipelines and Systems for Threshold-Avoiding Quantification of LC–MS/MS Data, Analytical Chemistry, 2021, 93, 32, 11215–11224.