An open-source Python package of the AlphaPept ecosystem from the Mann Labs at the Max Planck Institute of Biochemistry and the University of Copenhagen. To enable all hyperlinks in this document, please view it at GitHub.
An open-source Python package of the AlphaPept ecosystem from the Mann Labs at the Max Planck Institute of Biochemistry and the University of Copenhagen.
Figure: Deep learning workflow for quality scoring and protein intensity estimation. The system takes mass spectrometry features as input, uses a neural network to predict quality scores, and leverages these scores to improve protein intensity estimation accuracy by distinguishing between high and low-quality measurements.
QuantSelect was developed by the Mann Labs at the Max Planck Institute of Biochemistry and the University of Copenhagen and is freely available with an Apache License. External Python packages (available in the requirements folder) have their own licenses, which can be consulted on their respective websites.
QuantSelect can be installed and used on all major operating systems (Windows, macOS and Linux). There are two different types of installation possible:
- Pip installer: Choose this installation if you want to use QuantSelect as a Python package in an existing Python 3.9+ environment (e.g. a Jupyter notebook). The CLI can be installed with pip as well.
- Developer installer: Choose this installation if you are familiar with CLI tools, conda and Python. This installation allows access to all available features of QuantSelect and even allows to modify its source code directly. Generally, the developer version of QuantSelect outperforms the precompiled versions which makes this the installation of choice for high-throughput experiments.
QuantSelect can be installed in an existing Python 3.9+ environment with a single bash command. This bash command can also be run directly from within a Jupyter notebook by prepending it with a !:
pip install QuantSelectInstalling QuantSelect like this avoids conflicts when integrating it in other tools, as this does not enforce strict versioning of dependancies. However, if new versions of dependancies are released, they are not guaranteed to be fully compatible with QuantSelect. While this should only occur in rare cases where dependencies are not backwards compatible, you can always force QuantSelect to use dependancy versions which are known to be compatible with:
pip install "QuantSelect[stable]"NOTE: You might need to run pip install pip==21.0 before installing QuantSelect like this. Also note the double quotes ".
For those who are really adventurous, it is also possible to directly install any branch (e.g. @development) with any extras (e.g. #egg=QuantSelect[stable,development-stable]) from GitHub with e.g.
pip install "git+https://github.com/MannLabs/QuantSelect.git@development#egg=QuantSelect[stable,development-stable]"QuantSelect can also be installed in editable (i.e. developer) mode with a few bash commands. This allows to fully customize the software and even modify the source code to your specific needs. When an editable Python package is installed, its source code is stored in a transparent location of your choice. While optional, it is advised to first (create and) navigate to e.g. a general software folder:
mkdir ~/folder/where/to/install/software
cd ~/folder/where/to/install/softwareThe following commands assume you do not perform any additional cd commands anymore.
Next, download the QuantSelect repository from GitHub either directly or with a git command. This creates a new QuantSelect subfolder in your current directory.
git clone https://github.com/MannLabs/QuantSelect.gitFor any Python package, it is highly recommended to use a separate conda virtual environment, as otherwise dependancy conflicts can occur with already existing packages.
conda create --name QuantSelect python=3.9 -y
conda activate QuantSelectFinally, QuantSelect and all its dependancies need to be installed. To take advantage of all features and allow development (with the -e flag), this is best done by also installing the development dependencies instead of only the core dependencies:
pip install -e "./QuantSelect[development]"By default this installs loose dependancies (no explicit versioning), although it is also possible to use stable dependencies (e.g. pip install -e "./QuantSelect[stable,development-stable]").
By using the editable flag -e, all modifications to the QuantSelect source code folder are directly reflected when running QuantSelect. Note that the QuantSelect folder cannot be moved and/or renamed if an editable version is installed. In case of confusion, you can always retrieve the location of any Python module with e.g. the command import module followed by module.__file__.
There are two ways to use QuantSelect:
NOTE: The first time you use a fresh installation of QuantSelect, it is often quite slow because some functions might still need compilation on your local operating system and architecture. Subsequent use should be a lot faster.
The CLI can be run with the following command (after activating the conda environment with conda activate QuantSelect or if an alias was set to the QuantSelect executable):
QuantSelect -hIt is possible to get help about each function and their (required) parameters by using the -h flag.
QuantSelect can be imported as a Python package into any Python script or notebook with the command import QuantSelect.
A brief Jupyter notebook tutorial on how to use the API is also present in the nbs folder.
In case of issues, check out the following:
- Issues: Try a few different search terms to find out if a similar problem has been encountered before
- Discussions: Check if your problem or feature requests has been discussed before.
There are currently no plans to draft a manuscript.
If you like this software, you can give us a star to boost our visibility! All direct contributions are also welcome. Feel free to post a new issue or clone the repository and create a pull request with a new branch. For an even more interactive participation, check out the discussions and the the Contributors License Agreement.
See the HISTORY.md for a full overview of the changes made in each version.