Case Studies and Examples¶
Clustergrammer was developed to visualize high-dimensional biological data (e.g. genome-wide expression data), but it can also generally be applied to any high-dimensional data (e.g. a matrix). Below are links to several example case studies and examples using Clustergrammer.
Cancer Cell Line Encyclopedia Gene Expression Data¶
The Cancer Cell Line Encyclopedia (CCLE) is a publicly available project that has characterized (e.g. genetic characterization) over 1,000 cancer cell lines. We used Clustergrammer to re-analyze and visualize CCLE’s gene expression data in the CCLE Explorer. The CCLE Explorer allows users to explore the CCLE by tissue type and visualize the most commonly differentially expressed genes for each tissue type as an interactive heatmap. The CCLE Jupyter Notebook generates an overview of the CCLE gene expression data, investigates specific tissues, and explains how to use Enrichrgram to understand the biological functions of differentially expressed genes.
Zika Virus RNA-seq Data Visualization¶
Clustergrammer was used to visualize the results of an RNA-Seq data analysis pipeline within a Jupyter notebook: An open RNA-Seq data analysis pipeline tutorial with an example of reprocessing data from a recent Zika virus study (Wang et al.).
Single-Cell RNA-seq Data Visualization¶
Clustergrammer was used to visualize published single-cell gene expression data: Single-Cell RNA-seq Data Visualization (Olsson et al.). The visualization was produced using an Excel file provided alongside the figures.
Machine Learning and Miscellaneous Datasets¶
Clustergrammer was used to visualize several widely used machine learning Datasets and other miscellaneous Datasets:
These examples demonstrate the generality of heatmap visualizations and enable users to interactively explore familiar Datasets.