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 language | English (US) |
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Pages (from-to) | 782-790 |
Number of pages | 9 |
Journal | Journal of Proteome Research |
Volume | 18 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2019 |
Bibliographical note
Publisher Copyright:Copyright © 2018 American Chemical Society.
Keywords
- concordance
- integrative analysis
- mass spectrometry
- multiomics
- proteo-transcriptomics
- proteomics
- quantitation
- systems biology
- transcriptomics
- visualization