Abstract
Although cell morphology is often the gold standard for diagnosis and prognosis of many diseases, and conditions, it has seen limited application in combination with comprehensive molecular and functional characterization. This is largely due to the manual and subjective process of collecting cell morphology information and limited methods for sorting that do not perturb the cells. Here, we introduce the COSMOS platform, which is capable of high-throughput cell imaging and sorting, based on deep learning interpretation of high-content morphology information in realtime, yielding populations of cells that are label-free, viable, and minimally perturbed. We demonstrate the utility of the platform by enriching tumor cells and performing gene expression analysis on sorted cells showing concordance between morphological and molecular assessments.
One sentence summary A novel platform capable of high-throughput imaging and gently sorting cells using deep morphological assessment.
Competing Interest Statement
All authors are current or former employees at or are affiliated with Deepcell Inc.
