Workflow for Rapidly Extracting Biological Insights from Complex, Multicondition Proteomics Experiments with WGCNA and PloGO2

• DOI: 10.1021/acs.jproteome.0c00198
• Publication Date: 2020-05-14T22:45:45Z
• Authors: Jemma X. Wu; Dana Pascovici; Yunqi Wu; Adam K. Walker; Mehdi Mirzaei
• Keywords: Bioconductor

We describe a useful workflow for characterizing proteomics experiments incorporating many conditions and abundance data using the popular weighted gene correlation network analysis (WGCNA) approach functional annotation with PloGO2 R package, latter of which we have extended made available to Bioconductor. The can use quantitative from labeled or label-free was developed handle multiple files stemming partition pairwise comparisons. WGCNA similarly produce potentially large number clusters interest, also be functionally characterized PloGO2. Enrichment will identify subsets proteins topology scores ranking within these subsets. This naturally lead prioritized considered further as candidates interest validation in context complex experiments. demonstrate package on two published sets different biological systems (plant human plasma) platforms (sequential window acquisition all theoretical fragment-ion spectra (SWATH) tandem mass tag (TMT)): an effect drought rice over time generated TMT pediatric plasma sample set SWATH. In both, automated recapitulates key insights observations papers provides additional suggestions investigation. These findings indicate that combined updated is powerful method gain multifaceted