Knowledge graphs for drug discovery workshop

Abstract

In order to help clinical research organizations explore their genetic associations results, we developed the kgraph and sgraph packages to build and visualize knowledge graphs in Shiny with Sigma.js. Imagine you have a data frame of p-value associations between phenotypes and genes: using these packages, you can easily identify which genes are associated with several phenotypes. By selecting phenotypes, all associated genes are displayed, and the genes associated with several phenotypes are highlighted and spatially grouped. Nodes and edges are efficiently scaled to instantly give you a grasp of the most important information, while still enabling you to zoom in on specific points you want to explore. Additionally, we have added the ability to overlay supplementary nodes as drug information, to show e.g. their maximum clinical phase reached, to identify which drugs target which genes and what is the status of the drug development progress. The sgraph package provides an htmlwidget interface to Sigma.js graph visualization for use in Shiny and is available on CRAN since May 2024. The kgraph package focuses on building knowledge graphs and then calls the sgraph package. It is currently being packaged for CRAN submission, and the development version is available at https://gitlab.com/thomaschln/kgraph. It includes a Shiny app, of which a live version can be found at https://celehs.connect.hms.harvard.edu/kgraph/ Resources mentioned in the workshop: {opticskxi} OPTICS K-Xi Density-Based Clustering https://cran.r-project.org/package=opticskxi {kgraph} Knowledge Graphs R package https://cran.r-project.org/package=kgraph {kgraph} vignette https://cran.r-project.org/web/packages/kgraph/vignettes/kgraph.html Word embeddings in mental health (R/Medicine 2024 presentation recording) https://www.youtube.com/watch?v=LCK0UqQ1oK4

Workshop recorded as part of the 2024 R/Pharma Workshop Series