Drop-seq was first published in 2015, posing a revolution in single-cell RNA sequencing with an open-source, cost-effective, high-throughput analysis of gene transcripts. In this method, a highly diluted suspension of cells and barcoded beads is encapsulated in a water-in-oil droplet following double-Poisson statistics, aiming for a maximum encapsulation rate of one cell together with one bead, while keeping erroneous encapsulations of multiple cells or multiple beads together with one or more beads or cells, respectively, at a minimum. This decreases the efficiency and increases the cost per cell as more reagents are used. In this work, we present an approach to increase the number of desired encapsulation events, while decreasing erroneous encapsulations. Therefore, we use a special microfluidic analysis device in combination with a custom-made dielectrophoretic (DEP) sorting microchannel, enabling the detection and elimination of erroneous bead encapsulations, providing the opportunity to increase the concentration of beads to increase the number of desired encapsulation events (1 bead + 1 cell) considerably, while decreasing relevant erroneously encapsulations.
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