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IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of
Marc-Antoine Gerault1,2, Samuel Granjeaud2, Luc Camoin2
1Department of Oncology and Pathology, Karolinska Institutet, 171 77 Stockholm, Sweden.
Briefings in Bioinformatics
|April 1, 2024
Summary
Researchers developed IMPRINTS.CETSA, an R package and Shiny app for analyzing protein interactions. This tool simplifies data processing and introduces a novel scoring algorithm for identifying modulated proteins, enhancing proteome-level interaction studies.
Area of Science:
- Proteomics
- Systems Biology
- Biochemistry
Background:
- IMPRINTS-CETSA (Integrated Modulation of Protein Interaction States-Cellular Thermal Shift Assay) enables high-resolution study of protein interactions at the proteome level.
- Existing methods lack freely available, user-friendly software for analyzing IMPRINTS-CETSA data.
Purpose of the Study:
- To develop user-friendly software tools for the analysis of IMPRINTS-CETSA data.
- To introduce a novel algorithm for classifying modulated proteins based on a single-measure score.
Main Methods:
- Development of the IMPRINTS.CETSA R package for data preprocessing, normalization, and visualization.
- Creation of the IMPRINTS.CETSA.app, a Shiny interface for interactive analysis and interpretation.
- Implementation of a new algorithm for robust single-measure scoring of protein modulations.
Main Results:
- The IMPRINTS.CETSA R package provides a comprehensive framework for data analysis.
- IMPRINTS.CETSA.app offers seamless functional enrichment and database mapping.
- The new algorithm effectively classifies modulated proteins using a single, robust score, visualizing both numerical changes and statistical significance.
Conclusions:
- IMPRINTS.CETSA and IMPRINTS.CETSA.app provide essential, accessible tools for IMPRINTS-CETSA data analysis.
- The novel scoring algorithm enhances the identification and visualization of protein modulations.
- These freely available resources will advance proteome-level interaction studies.
