Package: MSstatsBioNet 1.5.1

Anthony Wu

MSstatsBioNet: Network Analysis for MS-based Proteomics Experiments

A set of tools for network analysis using mass spectrometry-based proteomics data and network databases. The package takes as input the output of MSstats differential abundance analysis and provides functions to perform enrichment analysis and visualization in the context of prior knowledge from past literature. Notably, this package integrates with INDRA, which is a database of biological networks extracted from the literature using text mining techniques.

Authors:Anthony Wu [aut, cre], Olga Vitek [aut]

MSstatsBioNet_1.5.1.tar.gz
MSstatsBioNet_1.5.1.zip(r-4.7)MSstatsBioNet_1.5.1.zip(r-4.6)MSstatsBioNet_1.5.1.zip(r-4.5)
MSstatsBioNet_1.5.1.tgz(r-4.6-any)MSstatsBioNet_1.5.1.tgz(r-4.5-any)
MSstatsBioNet_1.5.1.tar.gz(r-4.7-any)MSstatsBioNet_1.5.1.tar.gz(r-4.6-any)
MSstatsBioNet_1.5.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MSstatsBioNet/json (API)

# Install 'MSstatsBioNet' in R:
install.packages('MSstatsBioNet', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/vitek-lab/msstatsbionet/issues

Pkgdown/docs site:https://vitek-lab.github.io

On BioConductor:MSstatsBioNet-1.5.1(bioc 3.24)MSstatsBioNet-1.4.1(bioc 3.23)

immunooncologymassspectrometryproteomicssoftwarequalitycontrolnetworkenrichmentnetwork

6.94 score 2 stars 1 packages 12 scripts 12 exports 106 dependencies

Last updated from:e25917edd8. Checks:1 FAILURE, 7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksFAILURE276
linux-devel-x86_64NOTE240
source / vignettesOK295
linux-release-x86_64NOTE235
macos-release-arm64NOTE162
macos-oldrel-arm64NOTE124
windows-develNOTE161
windows-releaseNOTE156
windows-oldrelNOTE165
wasm-releaseOK141

Exports:annotateProteinInfoFromIndrabootstrapTopicModelscompareTopicModelscytoscapeNetworkcytoscapeNetworkOutputdecomposeSubnetworkByTopicdeleteEdgeFromNetworkexportNetworkToHTMLfilterSubnetworkByContextgetSubnetworkFromIndrapreviewNetworkInBrowserrenderCytoscapeNetwork

Dependencies:askpassbackportsbase64encbitopsbootbslibcachemcaToolscheckmateclicpp11crosstalkcurldata.tabledigestdplyrevaluatefarverfastmapfloatfontawesomefsgenericsggplot2ggrepelgluegplotsgtablegtoolshighrhtmltoolshtmlwidgetshttrisobandISOcodesjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevallgrlifecyclelimmalme4log4rmagrittrmarrayMASSMatrixMatrixExtramemoisemimeminqamlapiMSstatsMSstatsConvertnlmenloptropensslotelpillarpkgconfigplotlypreprocessCorepromisespurrrr2rR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrentrezRhpcBLASctlrlangrmarkdownrsparseS7sassscalesstatmodstopwordsstringistringrsurvivalsystext2vectibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunXMLxml2yaml

MSstatsBioNet Introduction
Installation | Purpose of MSstatsBioNet | Dataset | MSstats Convert from Upstream Dataset | MSstats Process and GroupComparison | MSstatsBioNet Analysis | ID Conversion | Subnetwork Query | Visualize Networks | Session info
Rendered fromMSstatsBioNet.Rmdusingknitr::rmarkdown

Last update: 2026-06-16
Started: 2024-07-25

PTM Analysis
Installation | Dataset | ID Conversion | Subnetwork Query | Network Visualization | Session info
Rendered fromPTM-Analysis.Rmdusingknitr::rmarkdown

Last update: 2026-06-16
Started: 2025-09-11

Visualization Engine with CytoscapeJS
Rendered fromCytoscape-Visualization.Rmdusingknitr::rmarkdown

Last update: 2026-06-16
Started: 2026-02-27

Filtering Subnetworks by Biological Context
Overview | Input Data | Building the Subnetwork | Step 1 — Annotate proteins with INDRA metadata | Step 2 — Retrieve the interaction subnetwork | Filtering by Context: Tag Count | Defining the Query | Filtered nodes | Filtered edges | Evidence with scores | Defining a cutoff | Filtering by Context: Cosine score | Choosing a score Cutoff | Session Info
Rendered fromFilter-By-Context.Rmdusingknitr::rmarkdown

Last update: 2026-03-11
Started: 2026-03-11

Readme and manuals

Help Manual

Help pageTopics
Populate Entity Information in Data Frame.populateEntityInformationInDataFrame
Populate entity grounding columns via Gilda.populateEntityInformationWithGilda
Populate entity grounding columns via INDRA cogex APIs.populateEntityInformationWithIndraCogex
Populate Kinase Info in Data Frame.populateKinaseInfoInDataFrame
Populate Phosphatase Info in Data Frame.populatePhophataseInfoInDataFrame
Populate Transcription Factor Info in Data Frame.populateTranscriptionFactorInfoInDataFrame
Populate Uniprot IDs in Data Frame.populateUniprotIdsInDataFrame
Validate Annotate Protein Info Input.validateAnnotateProteinInfoFromIndraInput
Annotate Protein Information from IndraannotateProteinInfoFromIndra
Bootstrap the topic decomposition to find each topic's robust top wordsbootstrapTopicModels
Test whether including PPIs changes topic structure beyond random chancecompareTopicModels
Render a Cytoscape network visualisationcytoscapeNetwork
Shiny output binding for cytoscapeNetworkcytoscapeNetworkOutput
Decompose a subnetwork into topic-specific subnetworks via joint NMFdecomposeSubnetworkByTopic
Delete an edge from a network edges data framedeleteEdgeFromNetwork
Export network data with Cytoscape visualizationexportNetworkToHTML
Filter a subnetwork by contextual relevancefilterSubnetworkByContext
Get subnetwork from INDRA databasegetSubnetworkFromIndra
Preview network in browserpreviewNetworkInBrowser
Render a Cytoscape network in a Shiny application. This function is used to render a Cytoscape network visualization within a Shiny application.renderCytoscapeNetwork