When manually gating files -- especially for large and complex panels or datasets with many files -- laboratory staff can end up adjusting gates for hours or sometimes even days, said Nicole Weit, Senior Technical Product Manager for Biodiscovery Flow Software.

"We've been on a relentless mission to stop the madness and provide a solution to these challenges, so that customers can level up their flow cytometry data analysis without having to be programmers."

According to the company, Cytobank Automatic gating can address the issue of inconsistencies among operators and reduce variability compared to manual gating. Also, depending on the complexity of the gating strategy, it can take up to 75% less time to complete compared to manual gating of the full dataset for population identification.

Cytobank Automatic gating allows lab staff to set up their own gating strategy on a set of files, train a model, and then reproducibly analyze more samples using the trained model. The model can then easily be shared with colleagues around the globe. When new data needs to be analyzed, users simply start a new automatic gating inference run with the trained model. This workflow saves users hands-on time, reduces variability, and empowers collaboration across institutions, said the company.