Package: alphaviz
AlphaVizAlphaVizis a cutting-edge browser-based interactive visualization tool allowing to visualize the processed mass spectrometry data acquired withBrukerinstrument. TheAlphaVizdashboard facilitates easy quality control of your analyzed samples and a clear inspection of the raw data of significant peptides/proteins.To enable all hyperlinks in this document, please view it atGitHub.AboutLicenseInstallationOne-click GUIPip installerDeveloper installerUsageGUICLIPython and jupyter notebooksTroubleshootingCitationsHow to contributeChangelogAboutSoftware tools such asMaxQuantorDIA-NNidentify and quantify high amounts of proteins. After downstream processing inPerseus,MSstatsor theClinical Knowledge Graph, differentially expressed proteins become possible candidates for biomarker discovery.AlphaVizis an automated visualization pipeline to link these identifications with the original raw data and easily assess their individual quality or the overall quality whole samples.An open-source Python package of the AlphaPept ecosystem from theMann Labs at the Max Planck Institute of Biochemistry. This project is built purely in Python using a new cutting-edgeHoloviz ecosystemand Plotly library to create interactive dashboards and plots.LicenseAlphaViz was developed by theMann Labs at the Max Planck Institute of Biochemistryand is freely available with anApache License. External Python packages (available in therequirementsfolder) have their own licenses, which can be consulted on their respective websites.InstallationAlphaViz can be installed and used on all major operating systems (Windows, macOS, Linux).
There are three different types of installation possible:One-click GUI installer:Choose this installation if you only want the GUI and/or keep things as simple as possible.Pip installer:Choose this installation if you want to use AlphaViz as a Python package in an existing Python 3.8 environment (e.g. a Jupyter notebook). If needed, the GUI and CLI can be installed with pip as well.Developer installer:Choose this installation if you are familiar with CLI tools,condaand Python. This installation allows access to all available features of AlphaViz and even allows to modify its source code directly. Generally, the developer version of AlphaViz outperforms the precompiled versions which makes this the installation of choice for high-throughput experiments.One-click GUIThe GUI of AlphaViz is a completely stand-alone tool that requires no knowledge of Python or CLI tools. Click on one of the links below to download the latest release for:WindowsmacOSLinuxOlder releases remain available on therelease page, but no backwards compatibility is guaranteed.IMPORTANT: Please refer to theGUI manualfor detailed instructions on the installation, troubleshooting and usage of the stand-alone AlphaViz GUI.PipAlphaViz 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!:pipinstallalphavizInstalling AlphaViz 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 AlphaViz. While this should only occur in rare cases where dependencies are not backwards compatible, you can always force AlphaViz to use dependancy versions which are known to be compatible with:pipinstall"alphaviz[gui-stable]"NOTE: You might need to runpip install pip==21.0before installing alphaviz 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=alphaviz[stable,development-stable]) from GitHub with e.g.pipinstall"git+https://github.com/MannLabs/alphaviz.git@development#egg=alphaviz[stable,development-stable]"DeveloperAlphaViz 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 AlphaViz repository from GitHub either directly or with agitcommand. This creates a new AlphaViz subfolder in your current directory.gitclonehttps://github.com/MannLabs/alphaviz.gitFor any Python package, it is highly recommended to use a separateconda virtual environment, as otherwisedependancy conflicts can occur with already existing packages.condacreate--namealphavizpython=3.8-y
condaactivatealphavizFinally, AlphaViz 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 dependenciesand/or thegui dependenciesinstead of only thecore dependencies:pipinstall-e"./alphaviz[gui,development]"By using the editable flag-e, all modifications to theAlphaViz source code folderare directly reflected when running AlphaViz. Note that the AlphaViz folder cannot be moved and/or renamed if an editable version is installed.UsageThere are two ways to use AlphaViz:GUIPythonNOTE: The first time you use a fresh installation of AlphaViz, 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.GUIIf the GUI was not installed through a one-click GUI installer, it can be activate with the followingbashcommand:alphavizguiNote that this needs to be prepended with a!when you want to run this from within a Jupyter notebook. When the command is run directly from the command-line, make sure you use the right environment (activate it with e.g.conda activate alphavizor set an alias to the binary executable (can be obtained withwhere alphavizorwhich alphaviz)).Python and Jupyter notebooksAlphaViz can be imported as a Python package into any Python script or notebook with the commandimport alphaviz.An ‘nbs’ folder in the GitHub repository contains several Jupyter Notebooks as tutorials regarding using AlphaViz as a Python package for all available pipelines: for DDA data analyzed with MaxQuant, for DIA data analyzed with DIA-NN, and for the targeted mode.TroubleshootingIn 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.CitationsPre-print published online: bioRxiv (2022), doi: 10.1101/2022.07.12.499676v1.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.