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Sci Data. 2017 Oct 10;4:170151. doi: 10.1038/sdata.2017.151.

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

Author information

Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, BD2K-LINCS Data Coordination and Integration Center (DCIC), Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.
Human Immune Monitoring Core, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.
Center for Structural and Functional Neuroscience, University of Montana, Missoula, Montana 59812, USA.
Cell Signaling Technology Inc., Danvers, Massachusetts 01923, USA.


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.

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