Package: alphabase
AlphaBaseAlphaBase provides all basic python functionalities for AlphaPept
ecosystem from theMann Labs at the Max Planck Institute of
Biochemistryand theUniversity of
Copenhagen. To enable
all hyperlinks in this document, please view it atGitHub. For documentation,
please seereadthedocs.AboutLicenseInstallationPip installerDeveloper installerUsageTroubleshootingCitationsHow to contributeChangelogAboutThe infrastructure package of AlphaX ecosystem for MS proteomics. It was first published with AlphaPeptDeep, seeCitations.Packages built upon AlphaBaseAlphaPeptDeep: deep learning framework for proteomics.AlphaRaw: raw data reader for different vendors.AlphaDIA: DIA search engine.PeptDeep-HLA: personalized HLA-binding peptide prediction.AlphaViz: visualization for MS-based proteomics.AlphaQuant: quantification for MS-based proteomics.CitationsWen-Feng Zeng, Xie-Xuan Zhou, Sander Willems, Constantin Ammar, Maria Wahle, Isabell Bludau, Eugenia Voytik, Maximillian T. Strauss & Matthias Mann. AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics. Nat Commun 13, 7238 (2022).https://doi.org/10.1038/s41467-022-34904-3LicenseAlphaBase was developed by theMann Labs at the Max Planck Institute of Biochemistryand theUniversity of Copenhagenand is
freely available with anApache License. External Python
packages (available in therequirementsfolder) have
their own licenses, which can be consulted on their respective websites.InstallationAlphaBase 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
AlphaBase as a Python package in an existing Python 3.8 environment
(e.g. a Jupyter notebook).Developer installer:Choose this installation if you
are familiar withcondaand
Python. This installation allows access to all available features of
AlphaBase and even allows to modify its source code directly.
Generally, the developer version of AlphaBase outperforms the
precompiled versions which makes this the installation of choice for
high-throughput experiments.PipAlphaBase can be installed in an existing Python 3.8 environment with a
singlebashcommand.Thisbashcommand can also be run directly
from within a Jupyter notebook by prepending it with a!:pipinstallalphabaseInstalling AlphaBase 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 AlphaBase. While this should only
occur in rare cases where dependencies are not backwards compatible, you
can always force AlphaBase to use dependancy versions which are known to
be compatible with:pipinstall"alphabase[stable]"NOTE: You might need to runpip install -U pipbefore installing
AlphaBase 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=alphabase[stable,development-stable]) from GitHub with e.g.pipinstall"git+https://github.com/MannLabs/alphabase.git@development#egg=alphabase[stable,development-stable]"DeveloperAlphaBase can also be installed in editable (i.e. developer) mode with a
fewbashcommands. 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/softwarecd~/folder/where/to/install/softwareThe following commands assume you do not perform any additionalcdcommands anymore.Next, download the AlphaBase repository from GitHub either directly or
with agitcommand. This creates a new AlphaBase subfolder in your
current directory.gitclonehttps://github.com/MannLabs/alphabase.gitFor any Python package, it is highly recommended to use a separateconda virtual environment, as
otherwisedependancy conflicts can occur with already existing
packages.condacreate--namealphabasepython=3.9-y
condaactivatealphabaseFinally, AlphaBase and all itsdependanciesneed to be
installed. To take advantage of all features and allow development (with
the-eflag), this is best done by also installing thedevelopment
dependenciesinstead of only
thecore dependencies:pipinstall-e"./alphabase[development]"By default this installs loose dependancies (no explicit versioning),
although it is also possible to use stable dependencies
(e.g.pip install -e "./alphabase[stable,development-stable]").By using the editable flag-e, all modifications to theAlphaBase
source code folderare directly reflected when running
AlphaBase. Note that the AlphaBase 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 commandimport modulefollowed bymodule.__file__.UsageTODOTroubleshootingIn case of issues, check out the following:Issues: Try a few
different search terms to find out if a similar problem has been
encountered beforeDiscussions:
Check if your problem or feature requests has been discussed before.How to contributeIf you like this software, you can give us astarto boost our
visibility! All direct contributions are also welcome. Feel free to post
a newissueor clone the
repository and create apull
requestwith a new branch.
For an even more interactive participation, check out thediscussionsand thethe Contributors License Agreement.ChangelogSee theHISTORY.mdfor a full overview of the changes made
in each version.