Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data

Nicolas Fernandez(Icahn School of Medicine at Mount Sinai), Gregory W. Gundersen(Icahn School of Medicine at Mount Sinai), Adeeb Rahman(Icahn School of Medicine at Mount Sinai), Mark L. Grimes(University of Montana), Klarisa Rikova(Cell Signaling Technology (United States)), Peter Hornbeck(Cell Signaling Technology (United States)), Avi Ma’ayan(Icahn School of Medicine at Mount Sinai)
Scientific Data
October 10, 2017
Cited by 278Open Access
Full Text

Abstract

Most tools developed to visualize hierarchically clustered heatmaps generate static images. Clustergrammer is a web-based visualization tool with interactive features such as: zooming, panning, filtering, reordering, sharing, performing enrichment analysis, and providing dynamic gene annotations. Clustergrammer can be used to generate shareable interactive visualizations by uploading a data table to a web-site, or by embedding Clustergrammer in Jupyter Notebooks. The Clustergrammer core libraries can also be used as a toolkit by developers to generate visualizations within their own applications. Clustergrammer is demonstrated using gene expression data from the cancer cell line encyclopedia (CCLE), original post-translational modification data collected from lung cancer cells lines by a mass spectrometry approach, and original cytometry by time of flight (CyTOF) single-cell proteomics data from blood. Clustergrammer enables producing interactive web based visualizations for the analysis of diverse biological data.


Related Papers

No related papers found

Powered by citation graph analysis