Systematic mapping of multiprotein complexes formed by protein-protein interactions (PPIs) can enhance our knowledge and mechanistic basis of how proteins function in the cells. Co-fractionation coupled with mass spectrometry (CF-MS) is gaining momentum as a cost-effective strategy for charting protein assemblies under native conditions using high-resolution chromatography separation techniques (e.g., size-exclusion and ion-exchange) without the need for antibodies or tagging of individual proteins. To capture high-quality PPIs from CF-MS co-elution profile, we have developed a well standardized and fully automated CF-MS data analysis software toolkit, referred to as MACP (Macromolecular Assemblies from the Co-elution Profile) in an open-source R package, beginning with the processing of raw co-elution data to reconstruction of high-confidence PPI networks via supervised machine-learning and underlying protein complexes using unsupervised approach.
You can install the MACP
from bioconductor using:
install.packages('MACP')
To install the development version in R
, run:
if(!requireNamespace("devtools", quietly = TRUE)) {
install.packages("devtools")
}
devtools::install_github("BabuLab-UofR/MACP")
For a detailed introduction to MACP, see the vignette.
Check the github page for source code
This project is licensed under the MIT License - see the LICENSE.md file for more details.
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