Abstract
SUMMARY: The increasing size and complexity of omics datasets can make effective visualization and interpretation very challenging. Differential expression datasets as from RNA-sequencing and proteomics can contain many thousands of features and even after filtering for significance there can be hundreds or thousands of features to consider. A common tool for visualizing this type of data is the volcano plot where each feature is plotted as the log2 transformed fold change along the x-axis and the negative log10 of a P-value along the y-axis. These plots provide a useful visualization of the largest and most significant changes, but the majority of the features are often crowded and overlapping near the "cone" of the volcano. In order to provide a biologically informative way to simplify the visualization and interpretation of these types of datasets we developed the Pathway Volcano tool. This R-Shiny based software utilizes the Reactome API to select specific pathways and then filters the volcano plots to show only the data associated with those pathways. In this manner, many of the significant features in the crowded section of the volcano plot can be revealed to support the impact of specified pathways. This tool provides a range of interactive features to interrogate the data along with the ability to download png files and tables with pathway associated data. AVAILABILITY AND IMPLEMENTATION: Pathway Volcano is a freely available R Shiny package. The program was developed in R version 4.3.3 using R Studio version 2024.09.1 Build 394. Running the app locally requires the packages ggplot2, plotly, shiny (https://shiny.posit.co/) dplyr (https://dplyr.tidyverse.org), and ReactomeContentServer (https://bioconductor.org/packages/ReactomeContentService4R/). The full code and documentation including example datasets are available at https://github.com/thoconne/PathwayVolcano and has been deposited in Zenodo under DOI 10.5281/zenodo.15425246.