Mining single-cell time-series datasets with Time Course Inspector

Abstract Summary Thanks to recent advances in live cell imaging of biosensors, microscopy experiments can generate thousands of single-cell time-series. To identify sub-populations with distinct temporal behaviours that correspond to different cell fates, we developed Time Course Inspector (TCI)—a u...

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Veröffentlicht in:Bioinformatics 2020-03, Vol.36 (6), p.1968-1969
Hauptverfasser: Dobrzyński, Maciej, Jacques, Marc-Antoine, Pertz, Olivier
Format: Artikel
Sprache:eng
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Zusammenfassung:Abstract Summary Thanks to recent advances in live cell imaging of biosensors, microscopy experiments can generate thousands of single-cell time-series. To identify sub-populations with distinct temporal behaviours that correspond to different cell fates, we developed Time Course Inspector (TCI)—a unique tool written in R/Shiny to combine time-series analysis with clustering. With TCI it is convenient to inspect time-series, plot different data views and remove outliers. TCI facilitates interactive exploration of various hierarchical clustering and cluster validation methods. We showcase TCI by analysing a single-cell signalling time-series dataset acquired using a fluorescent biosensor. Availability and implementation https://github.com/pertzlab/shiny-timecourse-inspector. Supplementary information Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btz846