QuanTP

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

Praveen Kumar, Priyabrata Panigrahi, James E Johnson, Wanda J Weber, Subina Mehta, Ray Sajulga, Caleb Easterly, Brian A Crooker, Mohammad Heydarian, Krishanpal Anamika, Timothy J Griffin, Pratik D Jagtap

Research output: Contribution to journalArticle

Abstract

Next-generation sequencing technologies, coupled to advances in mass-spectrometry-based proteomics, have facilitated system-wide quantitative profiling of expressed mRNA transcripts and proteins. Proteo-transcriptomic analysis compares the relative abundance levels of transcripts and their corresponding proteins, illuminating discordant gene product responses to perturbations. These results reveal potential post-transcriptional regulation, providing researchers with important new insights into underlying biological and pathological disease mechanisms. To carry out proteo-transcriptomic analysis, researchers require software that statistically determines transcript-protein abundance correlation levels and provides results visualization and interpretation functionality, ideally within a flexible, user-friendly platform. As a solution, we have developed the QuanTP software within the Galaxy platform. The software offers a suite of tools and functionalities critical for proteo-transcriptomics, including statistical algorithms for assessing the correlation between single transcript-protein pairs as well as across two cohorts, outlier identification and clustering, along with a diverse set of results visualizations. It is compatible with analyses of results from single experiment data or from a two-cohort comparison of aggregated replicate experiments. The tool is available in the Galaxy Tool Shed through a cloud-based instance and a Docker container. In all, QuanTP provides an accessible and effective software resource, which should enable new multiomic discoveries from quantitative proteo-transcriptomic data sets.

Original languageEnglish (US)
Pages (from-to)782-790
Number of pages9
JournalJournal of Proteome Research
Volume18
Issue number2
DOIs
StatePublished - Feb 1 2019

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Informatics
Galaxies
Software
Proteins
Visualization
Research Personnel
Proteomics
Mass spectrometry
Containers
Cluster Analysis
Mass Spectrometry
Genes
Experiments
Technology
Messenger RNA

Keywords

  • concordance
  • integrative analysis
  • mass spectrometry
  • multiomics
  • proteo-transcriptomics
  • proteomics
  • quantitation
  • systems biology
  • transcriptomics
  • visualization

PubMed: MeSH publication types

  • Journal Article

Cite this

QuanTP : A Software Resource for Quantitative Proteo-Transcriptomic Comparative Data Analysis and Informatics. / Kumar, Praveen; Panigrahi, Priyabrata; Johnson, James E; Weber, Wanda J; Mehta, Subina; Sajulga, Ray; Easterly, Caleb; Crooker, Brian A; Heydarian, Mohammad; Anamika, Krishanpal; Griffin, Timothy J; Jagtap, Pratik D.

In: Journal of Proteome Research, Vol. 18, No. 2, 01.02.2019, p. 782-790.

Research output: Contribution to journalArticle

Kumar, Praveen ; Panigrahi, Priyabrata ; Johnson, James E ; Weber, Wanda J ; Mehta, Subina ; Sajulga, Ray ; Easterly, Caleb ; Crooker, Brian A ; Heydarian, Mohammad ; Anamika, Krishanpal ; Griffin, Timothy J ; Jagtap, Pratik D. / QuanTP : A Software Resource for Quantitative Proteo-Transcriptomic Comparative Data Analysis and Informatics. In: Journal of Proteome Research. 2019 ; Vol. 18, No. 2. pp. 782-790.
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