AlphaPept

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AlphaPept: a modern and open framework for MS-based proteomics

Nature Communications.

Be sure to check out other packages of our ecosystem:

• alphatims: Fast access to TimsTOF data.
• alphamap: Peptide level MS data exploration.
• alphapeptdeep: Predicting properties from peptides.
• alphapeptstats: Downstream analysis of MS data
• alphaviz: Vizualization of MS data.

Windows Quickstart

1. Download the latest installer here, install and click the shortcut on the desktop. A browser window with the AlphaPept interface should open. In the case of Windows Firewall asking for network access for AlphaPept, please allow.
2. In the New Experiment, select a folder with raw files and FASTA files.
3. Specify additional settings such as modifications with Settings.
4. Click Start and run the analysis.

See also below for more detailed instructions.

Current functionality

| Feature | Implemented | |-----------------|----------------| | Type | DDA | | Filetypes | Bruker, Thermo | | Quantification | LFQ | | Isobaric labels | None | | Platform | Windows |

Linux and macOS should, in principle, work but are not heavily tested and might require additional work to set up (see detailed instructions below). To read Thermo files, we use Mono, which can be used on Mac and Linux. For Bruker files, we can use Linux but not yet macOS.

Python Installation Instructions

Requirements

We highly recommend the Anaconda or Miniconda Python distribution, which comes with a powerful package manager. See below for additional instructions for Linux and Mac as they require additional installation of Mono to use the RawFileReader.

AlphaPept can be used as an application as a whole or as a Python Package where individual modules are called. Depending on the use case, AlphaPept will need different requirements, and you might not want to install all of them.

Currently, we have the default requirements.txt, additional requirements to run the GUI gui and packages used for developing develop.

Therefore, you can install AlphaPept in multiple ways:

• The default alphapept
• With GUI-packages alphapept[gui]
• With pacakges for development alphapept[develop] (alphapept[develop,gui]) respectively

The requirements typically contain pinned versions and will be automatically upgraded and tested with dependabot. This stable version allows having a reproducible workflow. However, in order to avoid conflicts with package versions that are too strict, the requirements are not pinned when being installed. To use the strict version use the -stable-flag, e.g. alphapept[stable].

For end-users that want to set up a processing environment in Python, the "alphapept[stable,gui-stable]" is the batteries-included-version that you want to use.

Python

It is strongly recommended to install AlphaPept in its own environment. 1. Open the console and create a new conda environment: conda create --name alphapept python=3.8 2. Activate the environment: conda activate alphapept 3. Install AlphaPept via pip: pip install "alphapept[stable,gui-stable]". If you want to use AlphaPept as a package without the GUI dependencies and without strict version dependencies, use pip install alphapept.

If AlphaPept is installed correctly, you should be able to import AlphaPept as a package within the environment; see below.

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Linux

1. Install the build-essentials: sudo apt-get install build-essential.
2. Install AlphaPept via pip: pip install "alphapept[stable,gui-stable]". If you want to use AlphaPept as a package withouth the GUI dependencies and strict version dependencies use pip install alphapept.
3. Install libgomp.1 with sudo apt-get install libgomp1.

Bruker Support

4. Copy-paste the Bruker library for feature finding to your /usr/lib folder with sudo cp alphapept/ext/bruker/FF/linux64/alphapeptlibtbb.so.2 /usr/lib/libtbb.so.2.

Thermo Support

5. Install Mono from mono-project website Mono Linux. NOTE, the installed mono version should be at least 6.10, which requires you to add the ppa to your trusted sources!
6. Install pythonnet with pip install pythonnet>=2.5.2

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Mac

1. Install AlphaPept via pip: pip install "alphapept[stable,gui-stable]". If you want to use AlphaPept as a package withouth the GUI dependencies and strict version dependencies use pip install alphapept.

Bruker Support

Only supported for preprocessed files.

Thermo Support

2. Install brew and pkg-config: brew install pkg-config
3. Install Mono from mono-project website Mono Mac
4. Register the Mono-Path to your system: For macOS Catalina, open the configuration of zsh via the terminal:

• Type in cd to navigate to the home directory.
• Type nano ~/.zshrc to open the configuration of the terminal
• Add the path to your mono installation: export PKG_CONFIG_PATH=/usr/local/lib/pkgconfig:/usr/lib/pkgconfig:/Library/Frameworks/Mono.framework/Versions/Current/lib/pkgconfig:$PKG_CONFIG_PATH. Make sure that the Path matches to your version (Here 6.12.0)
• Save everything and execute . ~/.zshrc

4. Install pythonnet with pip install pythonnet>=2.5.2

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Developer

1. Redirect to the folder of choice and clone the repository: git clone https://github.com/MannLabs/alphapept.git
2. Navigate to the alphapept folder with cd alphapept and install the package with pip install . (default users) or with pip install -e . to enable developers mode. Note that you can use the different requirements here aswell (e.g. pip install ".[gui-stable]")

GPU Support

Some functionality of AlphaPept is GPU optimized that uses Nvidia’s CUDA. To enable this, additional packages need to be installed.

1. Make sure to have a working CUDA toolkit installation that is compatible with CuPy. To check type nvcc --version in your terminal.
2. Install cupy. Make sure to install the cupy version matching your CUDA toolkit (e.g. pip install cupy-cuda110 for CUDA toolkit 11.0.

Additional Notes

To access Thermo files, we have integrated RawFileReader into AlphaPept. We rely on Mono for Linux/Mac systems.

To access Bruker files, we rely on the timsdata-library. Currently, only Windows is supported. For feature finding, we use the Bruker Feature Finder, which can be found in the ext folder of this repository.

Notes for NBDEV

• For developing with the notebooks, install the nbdev package (see the development requirements)
• To facilitate navigating the notebooks, use jupyter notebook extensions. They can be called from a running jupyter instance like so: http://localhost:8888/nbextensions. The extensions collapsible headings and toc2 are very beneficial.

Standalone Windows Installer

To use AlphaPept as a stand-alone program for end-users, it can be installed on Windows machines via a one-click installer. Download the latest version here.

Docker

It is possible to run AlphaPept in a docker container. For this, we provide two Dockerfiles: Dockerfile_thermo and Dockerfile_bruker, depending on which filetypes you want to analyse. They are split because of drastically different requirements.

To run, navigate to the AlphaPept repository and rename the dockerfile you want to use, e.g. Dockerfile_thermo to Dockerfile.

• Build the image with: docker build -t docker-alphapept:latest .
• To run use docker run -p 8505:8505 -v /Users/username/Desktop/docker:/home/alphapept/ docker-alphapept:latest alphapept gui (Note that -v maps a local folder for convient file transfer)
• Access the AlphaPept GUI via localhost:8505 in your browser.
• Note 1: The Thermo Dockerfile is built on a Jupyter image, so you can also start a jupyter instance: docker run -p 8888:8888 -v /Users/username/Desktop/docker:/home/jovyan/ docker-alphapept:latest jupyter notebook --allow-root

Docker Troubleshooting on M1-Mac

• The Thermo dockerfile was tested on an M1-Mac. Resources were set to 18GB RAM and 2 CPUs, 200 GB disk
• It was possible to build the Bruker dockerfile with the platform tag --platform linux/amd64. However, it was very slow and the Bruker file is not recommended for an M1-Mac. Windows