RefQuant is an algorithm for Reference-based Quantification in multiplexed single cell/low input proteomics. It is applicable to data acquired with multiplexed data-independent acquisition (mDIA) using a reference channel, as described by Thielert et al. and visualized in figure 1 below. RefQuant currently takes DIA-NN processed mDIA files as input and generates an output table containing precursor intensities. For the analysis, RefQuant relies on a stable, higher-abundance reference channel that has been measured in every multiplexed run. The precursor quantities are derived by estimating the ratio to the reference channel based on the MS1 as well as the fragment information (see paper for details).
RefQuant 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.
RefQuant can 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 RefQuant repository from GitHub either directly or with a git command. This creates a new RefQuant subfolder in your current directory.
git clone https://github.com/MannLabs/refquant.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 refquant python=3.8 -y
conda activate refquantFinally, RefQuant 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 "./refquant[development]"By default this installs loose dependancies (no explicit versioning), although it is also possible to use stable dependencies (e.g. pip install -e "./refquant[stable,development-stable]").
By using the editable flag -e, all modifications to the refquant source code folder are directly reflected when running RefQuant. Note that the RefQuant 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__.
RefQuant can be imported as a Python package into any Python script or notebook with the command import refquant.
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.
Thielert, Marvin, et al. "Robust dimethyl-based multiplex-DIA workflow doubles single-cell proteome depth via a reference channel." bioRxiv (2022). (bioRxiv)
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.