Mining single-cell time-series datasets with Time Course Inspector.
Bioinformatics
; 36(6): 1968-1969, 2020 Mar 01.
Article
en En
| MEDLINE
| ID: mdl-38093482
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.
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1
Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2020
Tipo del documento:
Article
País de afiliación:
Suiza