Brasko C, Smith K, Molnar C, Farago N, Hegedus L, Balind A, Balassa T, Szkalisity A, Sukosd F, Kocsis K, Balint B, Paavolainen L, Enyedi MZ, Nagy I, Puskas LG, Haracska L, Tamas G, Horvath P
Nat Commun 9 (1) 226 [2018-01-15; online 2018-01-15]
Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample.