GigaScienceBioinformaticsPeer-reviewed journal article
TooManyCellsInteractive: a visualization tool for dynamic exploration of single-cell data
Conor KlamanniD, Christie J. LauiD, Javier Ruiz-RamíreziD, Gregory W. SchwartziD
Abstract
As single-cell sequencing data sets grow in size, visualizations of large cellular populations become difficult to parse and require extensive processing to identify subpopulations of cells. Managing many of these charts is laborious for technical users and unintuitive for non-technical users. To address this issue, we developed TooManyCellsInteractive (TMCI), a browser-based JavaScript application for visualizing hierarchical cellular populations as an interactive radial tree. TMCI allows users to explore, filter, and manipulate hierarchical data structures through an intuitive interface while also enabling batch export of high-quality custom graphics. Here we describe the software architecture and illustrate how TMCI has identified unique survival pathways among drug-tolerant persister cells in a pan-cancer analysis. TMCI will help guide increasingly large data visualizations and facilitate multi-resolution data exploration in a user-friendly way.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: trajectory inference
- research focus: differential expression
- approach: experimental assay
- Citations
- 4
- FWCI
- 0.54
- Field percentile
- top 41%
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