Exploring High-Dimensional Biological Data with Clustergrammer2

Visualizing biological data can be challenging. Heat maps are useful for showing the basic distribution of gene expression but interactivity is needed for additional, in-depth analysis. Clustergrammer2 is a visualization tool that allows users to perform more refined clustering on cell lines and genes.

In this webinar, Dr. Nicolas Fernandez, who worked on the original Clustergrammer and developed Clustergrammer2, will demonstrate how to use the latest version of this tool. Clustergrammer2, which is now available on Jupyter Notebook, can be used to explore and analyze various types of high-dimensional biological data (e.g., single-cell gene expression data) and share those results with colleagues.