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RPPAware: A software suite to preprocess, analyze and visualize reverse phase protein array data.

A Ranjitha Dhanasekaran1,2,3, Katheleen J Gardiner3,4,5

  • 1* Rocky Mountain Alzheimer's Disease Center, School of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, Colorado 80045, USA.

Journal of Bioinformatics and Computational Biology
|February 27, 2018
PubMed
Summary

RPPAware is a free, portable software tool designed for analyzing and visualizing protein expression data from Reverse Phase Protein Arrays (RPPA). This intuitive Java-based suite accelerates biological discovery by simplifying complex RPPA datasets.

Keywords:
RPPARPPAwaredata analysisprotein expressionproteomicsreverse phase protein arrays

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Area of Science:

  • Biotechnology
  • Bioinformatics
  • Genomics

Background:

  • Reverse Phase Protein Arrays (RPPA) generate large, complex datasets for protein expression profiling.
  • Efficient analysis and visualization tools are crucial for interpreting RPPA data.

Purpose of the Study:

  • To introduce RPPAware, a novel, free software suite for the analysis and visualization of RPPA data.
  • To provide an intuitive and portable tool that simplifies complex RPPA data handling.

Main Methods:

  • RPPAware was developed using Java and is portable, requiring no installation.
  • The software integrates R for advanced statistical analysis of RPPA data.
  • A case study involving Down syndrome mouse brain region data with 62 antibodies demonstrated the tool's utility.

Main Results:

  • RPPAware offers an intuitive interface for efficient RPPA data analysis and visualization.
  • The software successfully processed and analyzed RPPA data from a mouse model of Down syndrome.
  • The case study highlighted the tool's capability to accelerate biological discovery.

Conclusions:

  • RPPAware is an effective and user-friendly software solution for RPPA data analysis.
  • The tool's portability and integration with R enhance its utility for researchers.
  • RPPAware can significantly facilitate biological discovery by streamlining data interpretation.