Is manual gating a source of variability in your single-cell data analysis? Do you spend too much time on manually adjusting gates?

Join the Cytobank platform and find out how to train an automatic gating model using your marker panel and gating strategy, apply it to new data to faithfully identify the populations you defined without wasting time and effort on manual gate adjustments, and share it with others.

Reduced variability compared to manual gating

96 technical repeats were analyzed by four independent operators. An automatic gating model was trained on a subset of files (n=24) analyzed by operator 1 and subsequently applied to the remaining files by all four operators.

 
Shorter time to result

Time required for training and application of automatic model is 75% shorter compared to manual gating of the full dataset for population identification in 72 files with 7 gates.

 

Application Note
How to establish and evaluate machine learning- assisted automatic gating to improve reproducibility and reduce time spent on your flow cytometry data analysis.

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Whitepaper
Hypothesis-driven analysis of a 19-color deep immunophenotyping panel using automatic gating.

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Cytobank Brochure
Learn about the platform's capabilities for efficient analysis & secure sharing of high-complexity data.

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An introduction to Cytobank Automatic gating
Access our support portal to get step-by-step tutorial videos and articles about automatic gating.

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Cytobank Learning Center
Learn about the platform’s functionalities.

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