To 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. Note that
on Windows you must use zlibstatic
to avoid DLL path errors with the bindings.
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 update
Build the module and install it in your system:
# Installation
python3 setup.py install --user
# Development
python3 setup.py develop --user
Now it can be imported and used in python as follows:
import pastaq
raw_data = pastaq.read_mzxml(...)
Examples of the usage of the PASTAQ can be found in the examples
folder. 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.py
You can use any mzXML files and identifications in mzIdentML v1.1+. If no
identifications are available, remove the ident_path
from the input files
array or set it to 'none'
. You can find the files we used for testing and
development via ProteomeXchange, with identifier PXD024584.
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 visit the official website.
For an out of source build of the library, create a build directory and run cmake:
mkdir build
cd build
cmake ..
make
If you wish to enable the compilation of the tests you need to set up the
PASTAQ_ENABLE_TESTS
flag to 1. A limited number of automated test are
currently available but we are looking forward to improve this in the future.
mkdir build
cd build
cmake .. -DPASTAQ_ENABLE_TESTS=1
make
make test
Additionally, you can use the Ninja building tool for faster compilation times.
mkdir build
cd build
cmake .. -DPASTAQ_ENABLE_TESTS=1 -GNinja
ninja
ninja test
The 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.