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Title: Scalable, single cell multi-omics
Abstract
With increasing availability of the single-cell sequencing platforms, researchers are making exciting discoveries to transform biomedical research. However, current technologies can assess only handful of cells (1,000-10,000) due to limitation in the microfluidic encapsulation inefficiency. To date, most of the research has been focused on measuring RNA expression, often missing important phenotyping information. Biologists heavily relied on Flow cytometry or Mass cytometry to phenotype cells with limited number of markers. Here, I will introduce how the combinatorial indexing-based methods can be leveraged to achieve ultra-high throughput profiling of single-cell level multimodal expression patterns to topple technical barriers and discuss further how we envision single-cell perturbation study in genome-wide scale for the first time. As the sequencing cost continues to decrease, ultra high-throughput technology will democratize population-scale single cell studies and provide better insights into cellular interactions and heterogeneity in complex biological processes to delve deeper into human disease pathogenesis.