Initial recommendations for performing, benchmarking, and reporting single-cell proteomics experiments
We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories.
The Nature Methods white paper proposed best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics.
The white paper with community guidelines and recommendations is freely available at Nature Methods: Performing, benchmarking, and reporting single-cell proteomics experiments, Nature Methods, 20, 375--386 (2023) doi: 10.1038/s41592-023-01785-3
The preprint is available at the arXiv: Gatto et al., 2022.
For more information, contact Slavov Laboratory.
Running the code in this repository
Prerequisites: This recipe assumes a compute system with docker installed and access to the internet.
The code in the SCP recommendations repository can be run with the following sequence of commands:
git clone https://github.com/SlavovLab/SCP_recommendations.git
docker run \
--rm -it \
--volume $(pwd)/code:/code \
--volume $(pwd)/figs:/figs \
fabianegli/scp-recommendations-2022:1.0 \
Rscript "./code/make_figure2e.R"This will re-create the figures into the figs folder mounted to the docker container with the --volumes parameter in the command above.
The Dockerfile together with install_dependencies.R were used to produce the Docker image fabianegli/scp-recommendations-2022:1.0 which is available on Docker Hub.
License
The code is distributed by an MIT license.
Contributing
Please feel free to contribute to this project by opening an issue or pull request.
Help!
For any bugs, questions, or feature requests, please use the GitHub issue system to contact the developers.