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MACP

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.

Installation

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.

Contribute

Check the github page for source code

License

This project is licensed under the MIT License - see the LICENSE.md file for more details.

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Version

Install

install.packages('MACP')

Monthly Downloads

19

Version

0.1.0

License

BSD_3_clause + file LICENSE

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Maintainer

Matineh Rahmatbakhsh

Last Published

February 28th, 2023

Functions in MACP (0.1.0)

scaling

Column and Row-wise Normalization
subcellular.mtPPI

Keep Mitochondrial (mt) Proteins
Clust_Valid

Cluster Evaluation by External Measures
EliminateCpxRedundance

Hierarchical Clustering of Modules
enrichmentCPX

Functional Enrichment Analysis for Predicted Complexes
exampleData

Demo CF-MS data
MCL_clustering

MCL clustering
MCL_tuning

MCL Hyperparameters Tuning
cluster_tuning

ClusterONE Hyperparameters Tuning
ensemble_model

Predict Interactions via Ensemble Learning Method
calculate_PPIscore

Calculate Pairwise Protein Profile Similarity using Different Metrics
data_filtering

Data Filtering
refcpx

CORUM reference complexes
get_DenoisedNet

Denoising Predicted Protein-Protein Interactions
orthMappingCpx

Protein Complex Ortholog Mapping
getCPX

Fetch Complexes from the CORUM Database
get_clusters

Predict Complexes
generate_refInt

Generate Class Labels for Data Input Based on Gold Reference Set
predPPI_MACP

Predict Protein-Protein Interactions and Putative Complexes
impute_MissingData

Impute missing Values in Elution Profile Matrix
keepMT

Keep Mitochondrial (mt) Proteins