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Bioinformatics. 2019 Feb 15;35(4):706-708. doi: 10.1093/bioinformatics/bty676.

TIMING 2.0: high-throughput single-cell profiling of dynamic cell-cell interactions by time-lapse imaging microscopy in nanowell grids.

Author information

1
Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA.
2
Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA.
3
Center for Advanced Computing and Data Science and Department of Mechanical Engineering, University of Houston, Houston, TX, USA.
4
Division of Pediatrics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Abstract

MOTIVATION:

Automated profiling of cell-cell interactions from high-throughput time-lapse imaging microscopy data of cells in nanowell grids (TIMING) has led to fundamental insights into cell-cell interactions in immunotherapy. This application note aims to enable widespread adoption of TIMING by (i) enabling the computations to occur on a desktop computer with a graphical processing unit instead of a server; (ii) enabling image acquisition and analysis to occur in the laboratory avoiding network data transfers to/from a server and (iii) providing a comprehensive graphical user interface.

RESULTS:

On a desktop computer, TIMING 2.0 takes 5 s/block/image frame, four times faster than our previous method on the same computer, and twice as fast as our previous method (TIMING) running on a Dell PowerEdge server. The cell segmentation accuracy (f-number = 0.993) is superior to our previous method (f-number = 0.821). A graphical user interface provides the ability to inspect the video analysis results, make corrective edits efficiently (one-click editing of an entire nanowell video sequence in 5-10 s) and display a summary of the cell killing efficacy measurements.

AVAILABILITY AND IMPLEMENTATION:

Open source Python software (GPL v3 license), instruction manual, sample data and sample results are included with the Supplement (https://github.com/RoysamLab/TIMING2).

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
30084956
PMCID:
PMC6378937
[Available on 2020-02-15]
DOI:
10.1093/bioinformatics/bty676

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