pmartR 2.0: A Quality Control, Visualization, and Statistics Pipeline for Multiple Omics Datatypes
Journal Article
·
· Journal of Proteome Research
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
The pmartR (https://github.com/pmartR/pmartR) package was designed for the quality control (QC) and analysis of mass spectrometry (MS) data, tailored to specific characteristics of proteomic (isobaric or labelled), metabolomic, and lipidomic datasets. Since its initial release, the tool has been expanded to address the needs of its growing userbase and now includes QC and statistics for nuclear magnetic resonance (NMR) metabolomic data, and leverages the DESeq2, edgeR, and limma-voom R packages for some transcriptomic data analyses. These improvements have made progress towards a unified omics processing pipeline for ease of reporting and streamlined statistical purposes. The package’s statistics and visualization capabilities have also been expanded by adding support for paired data and by integrating pmartR with the trelliscopejs R package for the quick creation of trellis displays (https://github.com/hafen/trelliscopejs). Here, we present relevant examples of each of these enhancements to pmartR and highlight how each new feature benefits the omics community.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Grant/Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1968883
- Report Number(s):
- PNNL-SA-177968
- Journal Information:
- Journal of Proteome Research, Journal Name: Journal of Proteome Research Journal Issue: 2 Vol. 22; ISSN 1535-3893
- Publisher:
- American Chemical Society (ACS)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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