Installation

Oktoberfest can be installed on all three major platforms (Linux, MacOS, Windows).

An installer script is provided for Linux (installers for MacOS and Windows are currently prepared), which takes care of all dependencies. For MacOS and Windows, the Docker container or manual installation can be used.

Installer script (Debian / Ubuntu only)

The installer script automatically installs dependencies and creates a new conda environment for oktoberfest. The installation takes roughly 5 minutes and follows the steps outlined in the manual installation below. Get the installer and execute the script using

wget https://raw.githubusercontent.com/wilhelm-lab/oktoberfest/main/installer.sh -O install_oktoberfest.sh
bash install_oktoberfest.sh

The installer searches for an existing anaconda / miniconda installation. If none is found, it will download and install miniconda.

Docker Image

This is only recommended for experienced users and can take up to 30 minutes to install, depending on experience.

Prerequisites:

After cloning the repository of oktoberfest, checkout the branch you want to build the container from. The latest stable version is always on the main branch. Then build the container using:

make build

Manual installation

This is a step-by-step guide for the manual installation of all mandatory and optional dependencies which should roughly take up to 20 minutes if all dependencies are installed.

Install Python

Oktoberfest requires python >=3.9 and <=3.11. Best practice is to use a clean conda environment (Miniconda). Follow the installation guide for your operating system, then create a new environment using

conda create -y -n oktoberfest python==3.10

Optional dependencies

There are multiple optional dependencies depending on job types. Detailed notes and installation instructions can be found below.

Job type

Dependency

Notes

Pre-processing

ThermoRawFileParser

not required if only mzML files are provided

mono

required for ThermoRawFileParser to work on Linux/macOS

Rescoring

Percolator

Rescoring + refinement learning

DLomix

ThermoRawFileParser ThermoRawFileParser v1.4.3: For conversion of RAW to mzML format. Download and unpack the zip or tar.gz file. The default locations Oktoberfest expects the executable to be at /opt/compomics/ (Linux/MacOS) or the folder from which you want to execute Oktoberfest (Windows). You do not need this package if you only ever provide mzML files. However, it is recommended to let Oktoberfest convert RAW files for you, to ensure the mzML files are formatted in the way Oktoberfest expects it.

`mono` For ThermoRawFileParser to work on Linux, you also need to ensure mono is installed using

sudo apt -y update && sudo apt -y install mono-devel  # Debian / Ubuntu

For MacOS, follow the instructions provided by Mono.

Percolator Percolator v3.06.1: This is the tool Mokapot is based on. As it has more options and is generally more stable wrt. to FDR cutoffs and deduplication, it is recommended to use this tool instead of Mokapot. Installable packages are provided for Linux/MacOS/Windows.

DLomix DLomix is a Python framework for deep learning in proteomics. Oktoberfest uses DLomix to refinement-learn intensity predictors on input spectra. It is listed as an optional dependency and can be installed using

poetry install -E dlomix

Installing Oktoberfest

Oktoberfest is listed on the Python Package Index (PyPI) and can be installed with pip. Activate your conda environment (or skip this if you use a system wide python installation) and install the package (and optionally jupyterlab) using

conda activate oktoberfest
pip install oktoberfest jupyterlab

For local prediction & refinement learning, you have to install Oktoberfest with the dlomix extra:

conda activate oktoberfest
pip install oktoberfest[dlomix]

Installing xiFDR

Oktoberfest generates input files for xiFDR, which is required for FDR estimation of XL-MS data. It does not run xiFDR directly.

To install and run xiFDR, please follow the instructions at: