2020

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

Bioinformatics (Oxford, England) Dobrzyński M, Jacques MA, Pertz O
阅读原文 PDF DOI PubMed

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示意图生成中

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中文摘要

英文摘要

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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