MSstatsBioNet is an R/Bioconductor package for network analysis and enrichment of MSstats differential abundance results in the context of prior-knowledge biomolecular networks. It takes the output of MSstats (or MSstatsTMT / MSstatsPTM) differential abundance analysis, queries network databases for the interactions among the analyzed proteins, and filters, contextualizes, and visualizes the resulting subnetworks. Notably, it integrates with INDRA, a database of biological networks assembled from the literature using text mining, enabling interpretation of proteomic and phosphoproteomic results against past published knowledge.
MSstatsBioNet is part of the MSstats family of packages, developed and maintained by the Vitek Lab at Northeastern University. The package and its documentation are also available at msstats.org.
Installation
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("MSstatsBioNet")The development version can be installed directly from this repository:
remotes::install_github("Vitek-Lab/MSstatsBioNet")Quick Start
library(MSstatsBioNet)
# Example MSstats differential abundance results (groupComparison output)
input <- data.table::fread(system.file("extdata/groupComparisonModel.csv",
package = "MSstatsBioNet"))
# Retrieve the subnetwork of interactions among these proteins from INDRA
subnetwork <- getSubnetworkFromIndra(input)
head(subnetwork$nodes)
head(subnetwork$edges)
# Visualize the network (e.g. in Cytoscape, or export to HTML)
cytoscapeNetwork(subnetwork$nodes, subnetwork$edges)Input Formats
MSstatsBioNet works on differential abundance results, not raw search-tool output. Its main entry point, getSubnetworkFromIndra(), accepts the ComparisonResult table produced by the group-comparison functions across the MSstats ecosystem:
| Upstream package | Function producing input |
|---|---|
| MSstats | groupComparison() |
| MSstatsTMT | groupComparisonTMT() |
| MSstatsPTM | groupComparisonPTM() |
The input table provides, per protein and comparison, the log2 fold change, p-value, and adjusted p-value used for filtering and network coloring. UniProt identifiers can be annotated with annotateProteinInfoFromIndra().
- Databases supported: INDRA
-
Filtering options: p-value filter, context/topic-based filtering (
filterSubnetworkByContext()) -
Visualization options: Cytoscape Desktop (
cytoscapeNetwork()), in-browser preview (previewNetworkInBrowser()), standalone HTML export (exportNetworkToHTML()), and Shiny integration (cytoscapeNetworkOutput()/renderCytoscapeNetwork())
Getting Help / Reporting Bugs
- Questions about usage, statistical methods, or troubleshooting: please post to the MSstats Google Group. This is monitored by the development team and searchable, so it’s the fastest way to get help and to see if your question has already been answered.
- Bug reports and feature requests for this repository: please open a GitHub issue.
References
If you use MSstatsBioNet, please cite:
- Wu A, Kohler D, Navada P, Robbins J, Boyle G, Boshart A, Karis K, Neefjes J, Konvalinka A, Sarthy J, Pino L, Gyori B, Vitek O. MSstatsBioNet: Integrating Statistical Analyses with Prior Knowledge Biomolecular Networks for Quantitative Proteomics and Phosphoproteomics. bioRxiv. 2026. DOI: 10.64898/2026.07.09.737605
Funding
MSstats development has been supported by the Chan Zuckerberg Initiative’s Essential Open Source Software for Science.
License
MSstatsBioNet is released under the Artistic-2.0 license. However, its dependencies may have different licenses. Notably, INDRA is distributed under the BSD 2-Clause license, and INDRA’s knowledge sources may have different licenses for commercial applications. Please refer to the INDRA README for more information on its knowledge sources and their associated licenses.