1 Institute for Computational Biomedicine, Heidelberg University

1 Introduction

Database knowledge is essential for omics data analysis and modeling. Despite being an important factor, contributing to the outcome of studies, often subject to little attention. With OmniPath our aim is to raise awarness of the diversity of available resources and facilitate access to these resources in a uniform and transparent way. OmniPath has been developed in a close contact to mechanistic modeling applications and functional omics analysis, hence it is especially suitable for these fields. OmniPath has been used for the analysis of various omics data. In the Saez-Rodriguez group we often use it in a pipeline with our footprint based methods DoRothEA and PROGENy and our causal reasoning method CARNIVAL to infer signaling mechanisms from transcriptomics data.

One recent novelty of OmniPath is a collection of intercellular communication interactions. Apart from simply merging data from existing resources, OmniPath defines a number of intercellular communication roles, such as ligand, receptor, adhesion, enzyme, matrix, etc, and generalizes the terms ligand and receptor by introducing the terms transmitter, receiver and mediator. This unique knowledge base is especially adequate for the emerging field of cell-cell communication analysis, typically from single cell transcriptomics, but also from other kinds of data.

2 Overview

2.1 Pre-requisites

No special pre-requisites apart from basic knowledge of R. OmniPath, the database resource in the focus of this workshop has been published in [1,2], however you don’t need to know anything about OmniPath to benefit from the workshop. In the workshop we will demonstrate the R/Bioconductor package OmnipathR. If you would like to try the examples yourself we recommend to install the latest version of the package before the workshop:


2.2 Participation

In the workshop we will present the design and some important features of the OmniPath database, so can be confident you get the most out of it. Then we will demonstrate further useful features of the OmnipathR package, such as accessing other resources, building graphs. Participants are encouraged to experiment with the examples and shape the contents of the workshop by asking questions. We are happy to recieve questions and topic suggestions by email also before the workshop. These could help us to adjust the contents to the interests of the participants.

2.3 R / Bioconductor packages used

  • OmnipathR
  • igraph
  • dplyr

2.4 Time outline

Total: 45 minutes

Activity Time
OmniPath database overview 5m
Network datasets 10m
Other OmniPath databases 5m
Intercellular communication 10m
Igraph integration 5m
Further resources 10m

2.5 Workshop goals and objectives

In this workshop you will get familiar with the design and features of the OmniPath databases. For example, to know some important details about the datasets and parameters which help you to query the database the most suitable way according to your purposes. You will also learn about functionalities of the OmnipathR package which might make your work easier.

2.6 Learning goals

  • Learn about the OmniPath database, its contents and how it can be useful
  • Get a picture about the OmnipathR package capabilities
  • Learn about the datasets and parameters of various OmniPath query types

2.7 Learning objectives

  • Try examples of each OmniPath query type with various parameters
  • Build igraph networks, search for paths
  • Access some further interesting resources

3 Workshop

Here we will publish the workshop contents with code examples.

Session info

## R version 4.1.0 (2021-05-18)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.13-bioc/R/lib/
## LAPACK: /home/biocbuild/bbs-3.13-bioc/R/lib/
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_GB              LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## other attached packages:
## [1] BiocStyle_2.20.2
## loaded via a namespace (and not attached):
##  [1] bookdown_0.23       digest_0.6.27       R6_2.5.1           
##  [4] jsonlite_1.7.2      magrittr_2.0.1      evaluate_0.14      
##  [7] stringi_1.7.3       rlang_0.4.11        jquerylib_0.1.4    
## [10] bslib_0.2.5.1       rmarkdown_2.10      tools_4.1.0        
## [13] stringr_1.4.0       xfun_0.25           yaml_2.2.1         
## [16] compiler_4.1.0      BiocManager_1.30.16 htmltools_0.5.1.1  
## [19] knitr_1.33          sass_0.4.0


[1] D Turei, A Valdeolivas, L Gul, N Palacio-Escat, M Klein, O Ivanova, M Olbei, A Gabor, F Theis, D Modos, T Korcsmaros and J Saez-Rodriguez (2021) Integrated intra- and intercellular signaling knowledge for multicellular omics analysis. Molecular Systems Biology 17:e9923

[2] D Turei, T Korcsmaros and J Saez-Rodriguez (2016) OmniPath: guidelines and gateway for literature-curated signaling pathway resources. Nature Methods 13(12)