Computational Pipeline for Analysis of Biomedical Networks with BioNAR

Abstract

AbstractIn a living cell, proteins interact to assemble both transient and constant molecular complexes, which transfer signals/information around internal pathways. Modern proteomic techniques can identify the constituent components of these complexes, but more detailed analysis demands a network approach linking the molecules together and analyzing the emergent architectural properties. The Bioconductor package BioNAR combines a selection of existing R protocols for network analysis with newly designed original methodological features to support step‐by‐step analysis of biological/biomedical . Critically, BioNAR supports a pipeline approach whereby many networks and iterative analyses can be performed. Here we present a network analysis pipeline that starts from initiating a network model from a list of components/proteins and their interactions through to identifying its functional components based solely on network topology. We demonstrate that BioNAR can help users achieve a number of network analysis goals that are difficult to achieve anywhere else. This includes how users can choose the optimal clustering algorithm from a range of options based on independent annotation enrichment, and predict a protein's influence within and across multiple subcomplexes in the network and estimate the co‐occurrence or linkage between metadata at the network level (e.g., diseases and functions across the network, identifying the clusters whose components are likely to share common function and mechanisms). The package is freely available in Bioconductor release 3.17: https://bioconductor.org/packages/3.17/bioc/html/BioNAR.html. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.Basic Protocol 1: Creating and annotating the networkSupport Protocol 1: Installing BioNAR from RStudioSupport Protocol 2: Building the sample network from synaptome.dbBasic Protocol 2: Network properties and centralityBasic Protocol 3: Network communitiesBasic protocol 4: Choosing the optimal clustering algorithm based on the enrichment with annotation termsBasic Protocol 5: Influencing network components and bridgenessBasic Protocol 6: Co‐occurrence of the annotations