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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

1
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.
2
Human Immune Monitoring Core, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA.
3
Center for Structural and Functional Neuroscience, University of Montana, Missoula, Montana 59812, USA.
4
Cell Signaling Technology Inc., Danvers, Massachusetts 01923, USA.

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.

PMID:
28994825
PMCID:
PMC5634325
DOI:
10.1038/sdata.2017.151
[Indexed for MEDLINE]
Free PMC Article

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