Pathway Commons 2019 Update: integration, analysis and exploration of pathway data

Abstract

Pathway Commons (https://www.pathwaycommons.org) is an integrated resource of publicly available information about biological pathways including biochemical reactions, assembly of biomolecular complexes, transport and catalysis events and physical interactions involving proteins, DNA, RNA, and small molecules (e.g. metabolites and drug compounds). Data is collected from multiple providers in standard formats, including the Biological Pathway Exchange (BioPAX) language and the Proteomics Standards Initiative Molecular Interactions format, and then integrated. Pathway Commons provides biologists with (i) tools to search this comprehensive resource, (ii) a download site offering integrated bulk sets of pathway data (e.g. tables of interactions and gene sets), (iii) reusable software libraries for working with pathway information in several programming languages (Java, R, Python and Javascript) and (iv) a web service for programmatically querying the entire dataset. Visualization of pathways is supported using the Systems Biological Graphical Notation (SBGN). Pathway Commons currently contains data from 22 databases with 4794 detailed human biochemical processes (i.e. pathways) and ∼2.3 million interactions. To enhance the usability of this large resource for end-users, we develop and maintain interactive web applications and training materials that enable pathway exploration and advanced analysis.

Functional in vivo and in vitro effects of 20q11.21 genetic aberrations on hPSC differentiation

“…Network propagation analysis 27 investigated the UP- or DOWN-DEG cascaded genes. The diffusr R package ( https://cran.r-project.org/package=diffusr ) considered UP- or DOWN DEGs as seed genes and propagated the influence of each of the seed genes to the other genes on a protein–protein interaction network, Pathway Commons 58 . Then, the top 500 and 1500 influenced genes were selected for each of the UP- or DOWN-cascaded DEGs.…”

Transcriptomic Profiling for the Autophagy Pathway in Colorectal Cancer

“…In brief, we applied the Ensemble of Gene Set Enrichment Analyses (EGSEA) method for gene set testing in the RNA-seq dataset by comparing tumor versus tumor-adjacent tissue [ 64 ]. We utilized the analysis of four prominent GSE algorithms: camera, fry, ora, and z-score to calculate the collective significance scores for each gene set (we used 2055 Human Reactome definitions from January 2020) [ 65 ]. Gene sets were ordered by median ranking (median across the ranks assigned by four selected methods).…”

netboxr: Automated discovery of biological process modules by network analysis in R

“…Beyond the base functions, netboxr includes several additions to simplify and expand its use. These include 1) instructions for retrieving and processing genomic alterations such as mutations and copy number alterations from data repositories such as cBioPortal [ 6 , 7 ] or Genomic Data Commons (GDC) [ 3 ], 2) instructions to use pathway data (i.e., genes or gene products with interactions) via the paxtoolsr Pathway Commons package [ 8 ] or from resources such as the STRING pathway database [ 9 ], 3) functionality to switch between the discovery of modules using various algorithms for detection of network communities from the igraph package [ 10 ] and 4) guidance on functionally annotating netboxr-derived modules using the ClusterProfiler package [ 11 ]. netboxr was implemented in R and can be installed through the BiocManager package manager from Bioconductor ( bioconductor.org ).…”