| Description |
Droplet microfluidics based single-cell combinatorial indexing sequencing represents an attractive way to balance cost, scalability, robustness, and accessibility. However, current methods need a tailored protocol for specific modality respectively, which may limit their potential of automation. Here, we introduce UDA-seq, universal droplet microfluidics based combinatorial indexing for massive-scale single-cell multimodal sequencing. We demonstrate that when necessary, UDA-seq enables effectively generating more than 100,000 single-cell data in a single-channel experiment of droplet microfluidics. Meanwhile, UDA-seq provides a universal workflow for accomplishing several multimodal tasks, including single-cell co-assay of RNA and VDJ, RNA and ATAC, and RNA and CRISPR guide RNA. Our approach represents a broadly applicable strategy for boosting the throughput and systematically "rewriting" most of existing droplet microfluidics based single-cell multimodal methods. |
