Dataset Information

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

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.

SUBMITTER: Lu H

PROVIDER: S-EPMC6378937 | biostudies-literature |

REPOSITORIES: biostudies-literature

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