A comprehensive R client for the OmniPath database and integrated biological knowledge resources, enabling systematic access to molecular interaction networks, signaling pathways, and functional annotations for systems biology research.

📖 Full Documentation: https://Zaoqu-Liu.github.io/OmnipathR/

OmnipathR provides programmatic access to the OmniPath web service (https://omnipathdb.org/) and integrates data from over 100 original resources, facilitating multi-omics data analysis and network-based computational biology workflows.

• Molecular Interactions: Protein-protein interactions (PPIs), transcription factor-target gene relationships, and miRNA-mRNA regulatory networks
• Post-translational Modifications: Enzyme-substrate relationships including phosphorylation, ubiquitination, and other PTM events
• Protein Complexes: Comprehensive database of >22,000 curated protein complexes
• Functional Annotations: Subcellular localization, protein function, tissue expression, and structural features
• Intercellular Communication: Ligand-receptor interactions and cell-cell communication annotations
• Multi-organism Support: Human, mouse, and rat with orthology translation capabilities

OmnipathR provides unified access to multiple databases including:

install.packages("OmnipathR", repos = "https://zaoqu-liu.r-universe.dev")

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# Release version
BiocManager::install("OmnipathR")

# Development version
BiocManager::install("OmnipathR", version = "devel")

if (!requireNamespace("remotes", quietly = TRUE))
    install.packages("remotes")

remotes::install_github("Zaoqu-Liu/OmnipathR")

library(OmnipathR)

# Retrieve protein-protein interactions
interactions <- omnipath(resources = c("SignaLink3", "SIGNOR"))

# Retrieve enzyme-substrate relationships
enzsub <- enzyme_substrate(resources = c("PhosphoSite", "SIGNOR"))

# Retrieve protein complex data
complexes <- complexes()

# Retrieve functional annotations
annotations <- annotations(
    proteins = c("TP53", "EGFR", "AKT1"),
    resources = "HPA_subcellular"
)

# Retrieve intercellular communication data
intercell <- intercell()

OmnipathR integrates seamlessly with igraph for network analysis:

# Convert to igraph object
network <- interaction_graph(interactions)

# Find shortest paths
paths <- find_all_paths(
    graph = network,
    start = c("EGFR", "ERBB2"),
    end = c("AKT1", "MTOR"),
    attr = "name"
)

# Extract giant component
gc <- giant_component(network)

Comprehensive ID mapping across multiple identifier systems:

# Translate UniProt IDs to gene symbols
translated <- translate_ids(
    data.frame(uniprot = c("P00533", "P04637")),
    uniprot, genesymbol
)

# Cross-organism orthology translation
mouse_orthologs <- orthology_translate_column(
    data,
    column = "uniprot",
    target_organism = "mouse",
    source_organism = "human"
)

If you use OmnipathR in your research, please cite:

Türei D, Korcsmáros T, Saez-Rodriguez J. OmniPath: guidelines and gateway for literature-curated signaling pathway resources. Nature Methods 2016;13:966-967. doi:10.1038/nmeth.4077

Türei D, Valdeolivas A, Gul L, Palber N, Ivanova O, Gábor A, et al. Integrated intra- and intercellular signaling knowledge for multicellular omics analysis. Molecular Systems Biology 2021;17:e9923. doi:10.15252/msb.20209923

We welcome contributions! Please submit issues and pull requests on GitHub:

• Bug Reports: https://github.com/Zaoqu-Liu/OmnipathR/issues
• Feature Requests: https://github.com/Zaoqu-Liu/OmnipathR/issues

This project is licensed under the MIT License - see the LICENSE file for details.

OmnipathR is developed and maintained by the Saez Lab at Heidelberg University.