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QuanTP: A Software Resource for Quantitative Proteo-Transcriptomic Comparative Data Analysis and Informatics.

Praveen Kumar1,2, Priyabrata Panigrahi3, James Johnson4

  • 1Bioinformatics and Computational Biology Program , University of Minnesota-Rochester , Rochester , Minnesota 55904 , United States.

Journal of Proteome Research
|December 25, 2018
PubMed
Summary
This summary is machine-generated.

QuanTP software integrates quantitative proteo-transcriptomic data, enabling researchers to analyze gene and protein expression levels. This tool aids in discovering post-transcriptional regulation and disease mechanisms.

Keywords:
concordanceintegrative analysismass spectrometrymultiomicsproteo-transcriptomicsproteomicsquantitationsystems biologytranscriptomicsvisualization

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Area of Science:

  • Multiomics
  • Systems Biology
  • Bioinformatics

Background:

  • Quantitative profiling of mRNA transcripts and proteins is advanced by next-generation sequencing and mass spectrometry.
  • Proteo-transcriptomic analysis reveals discordant gene product responses to perturbations, indicating potential post-transcriptional regulation.
  • Understanding biological and pathological disease mechanisms requires insights into these discordant responses.

Purpose of the Study:

  • To develop a user-friendly software solution for statistical analysis and interpretation of proteo-transcriptomic data.
  • To provide tools for assessing transcript-protein abundance correlation and visualizing results.
  • To facilitate multiomic discoveries from quantitative proteo-transcriptomic datasets.

Main Methods:

  • Development of the QuanTP software within the Galaxy platform.
  • Implementation of statistical algorithms for transcript-protein correlation analysis (single pairs and cohorts).
  • Inclusion of outlier identification, clustering, and diverse visualization functionalities.

Main Results:

  • QuanTP offers a suite of tools for proteo-transcriptomics, compatible with single experiment or two-cohort analyses.
  • The software provides statistical assessment of transcript-protein abundance correlation.
  • Results visualization and interpretation features are integrated within the Galaxy platform.

Conclusions:

  • QuanTP is an accessible and effective software resource for proteo-transcriptomic analysis.
  • The tool enables new multiomic discoveries by facilitating the interpretation of quantitative proteo-transcriptomic data.
  • QuanTP supports researchers in uncovering post-transcriptional regulation and disease mechanisms.