Integrated intra- and intercellular signaling knowledge for multicellular omics analysis

Abstract

Molecular knowledge of biological processes is a cornerstone in the analysis of omics data. Applied to single-cell data, such analyses can provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across different resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources in a single database. It covers the interactions and roles of proteins in inter- and intracellular signal transduction, as well as transcriptional and post-transcriptional regulation. We also provide a comprehensive collection of protein complexes and rich annotations on the properties of proteins, including function, localization, and role in diseases. The resource is available for human, and via homology translation for mouse and rat. The data is accessible via the web service of OmniPath, a Cytoscape plugin, and packages in R/Bioconductor and Python, providing convenient access options for both computational and experimental scientists. Our resource provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications to study SARS-CoV-2 infection and ulcerative colitis.

A Detailed Catalogue of Multi-Omics Methodologies for Identification of Putative Biomarkers and Causal Molecular Networks in Translational Cancer Research

“…In addition, the SignaLink 2 resource [ 123 ] is a signaling pathway database with multi-layered regulatory networks for the interpretation of multi-omics studies. Finally, the Omnipath database [ 124 ] is one of the richest sources regarding protein-protein interactions, including more than 100 knowledge resources for 20,000 human proteins and 16,500 complexes.…”

“…For this purpose there are various recent tools and databases that perform pathway analysis and provide prior knowledge on molecular biology to construct intracellular communication networks well-suited for multi-omics functional annotation. These include but are not limited to SignaLink 2.0 [ 123 ], OmniPath [ 124 , 194 ], ReactomeGSA [ 195 ] and ActivePathways [ 196 ]. Moreover, incorporation of prior knowledge from clinical data portals could further facilitate the prioritization of features or signatures from multimodal studies, which could serve as putative biomarkers.…”

Squidpy: a scalable framework for spatial single cell analysis

“…In our implementation, we also include the option of taking the mean expression of all molecules in the complex. Our implementation also employs Omnipath 13 as ligand-receptor interaction annotatiojn. A larger database that contains the original CellphoneDB database together with 5 other resources (see Turei et al 13 ).…”

“…Our implementation also employs Omnipath 13 as ligand-receptor interaction annotatiojn. A larger database that contains the original CellphoneDB database together with 5 other resources (see Turei et al 13 ). Finally, our implementation leverages just-in-time compilation with Numba 11 to achieve greater performances in computation time (see Supplementary figure 1 ).…”

Identification of phenotype-specific networks from paired gene expression-cell shape imaging data

“…The ‘costs’ associated with each edge in the regulatory network were the inverse of the number of sources linked to each regulatory connection scaled between 1 and 0, such that the more the number of citations for an edge, the lower the cost. For the base network used by the algorithm, we used the comprehensive biological prior knowledge database, Omnipath (Türei et al, 2016), extracted using the R package OmnipathR (Türei et al, 2020). We set each prize for significant TFs or signaling pathways to 100 and used a random variant of the PCSF algorithm with the result being the union of subnetworks obtained on each run (30 iterations) after adding random noise to the edge costs each time (5%).…”