From the website https://hafen.github.io/trelliscopejs/: "Trelliscope is a scalable, flexible, interactive approach to visualizing data. The trelliscopejs R package contains methods that make it easy to create a Trelliscope display. High-level functions are available for creating displays from within dplyr (via summarise()) or ggplot2 (via facet_trelliscope()) workflows." This presentation will focus on the fast method for trelliscope implementation and a brief overview of the workflow for custom implementations.
Presenter: Rachel Richardson is a data scientist for the Data Science and Biostatistics team at Pacific Northwest National Laboratory. She works on various bioinformatics projects. Her previous professional work includes working as a QC analyst for Seattle Genetics and in a microbial research lab during her undergraduate studies. Richardson’s work typically focuses on workflow development for biological projects, often requiring application and package development, as well as interpretation of results. Current projects of interest include developing a user interface for multi-omics application of pmartR and a QuickStarter project relating electromagentic imaging of facemasks to overall performance.