Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput.
Massively parallel digital transcriptional profiling of single cells. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Scaling single-cell genomics from phenomenology to mechanism. A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling-selecting representative methods based on their usage and our expertise and resources to prepare libraries-including two low-throughput and five high-throughput methods. However, these methods have not been systematically and comprehensively benchmarked.
The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts.
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