April 11, 2023
Journal Article

pmartR 2.0: A Quality Control, Visualization, and Statistics Pipeline for Multiple Omics Datatypes

Abstract

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.

Published: April 11, 2023

Citation

Degnan D.J., K.G. Stratton, R.E. Richardson, D.M. Claborne, E.A. Martin, N.A. Johnson, and D.T. Leach, et al. 2023. pmartR 2.0: A Quality Control, Visualization, and Statistics Pipeline for Multiple Omics Datatypes. Journal of Proteome Research 22, no. 2:570–576. PNNL-SA-177968. doi:10.1021/acs.jproteome.2c00610

Research topics