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Rtpca: an R package for differential thermal proximity coaggregation analysis.

Nils Kurzawa^1,2, André Mateus¹, Mikhail M Savitski¹

¹European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany.

Bioinformatics (Oxford, England)

|July 28, 2020

Summary

Rtpca is a new R package for identifying protein-protein interactions (PPIs) using thermal proteome profiling data. It provides accessible tools for analyzing PPI predictive performance and integrating with existing R packages.

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Area of Science:

Proteomics
Bioinformatics
Computational Biology

Background:

Protein-protein interactions (PPIs) are crucial for cellular functions.
Thermal proteome profiling (TPP) is an experimental technique to study PPIs.
Analyzing TPP data for PPI inference requires specialized computational tools.

Purpose of the Study:

To introduce Rtpca, an R package for inferring PPIs from TPP data.
To provide user-friendly methods for analyzing PPI predictive performance.
To facilitate integration with existing R-based bioinformatics workflows.

Main Methods:

Implementation of algorithms for PPI inference from single-condition or differential TPP experiments.
Utilizes the thermal proximity coaggregation approach.
Development of tools for dataset exploration and performance evaluation.

Main Results:

Rtpca offers a robust framework for PPI inference from TPP data.
The package enables assessment of PPI predictive performance.
Seamless integration with other R packages is supported.

Conclusions:

Rtpca enhances the analysis of thermal proteome profiling data for PPI discovery.
The package democratizes advanced PPI inference methods for researchers.
Rtpca is a valuable addition to the R ecosystem for systems biology research.