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Accessible and accurate cytometry analysis using fluorescence microscopes

Foyt, D.; Kuang, Y.; Rehem, S.; Yserentant, K.; Huang, B.

2025-01-24 cell biology
10.1101/2025.01.22.634380 bioRxiv
Show abstract

We have developed a method along with a python-based analysis tool to capture images and produce flow cytometry like data utilizing simple accessible microscopes. Utilizing the recently developed generalist algorithms for cell segmentation, our approach easily segments semi-adherent or suspended cells facilitating quantification of fluorescent intensity similar to flow cytometry. We have shown that our approach exhibits similar speed and enhanced sensitivity when compared to typical flow cytometry. The utility of our approach is demonstrated by screening a set of 88 prime editing conditions utilizing the integration of mNeonGreen11 as a reporter.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.