Highlights
- Simple, two-step method based on an improved experimental protocol for scRNA-Seq
- Increases observed mean counts and removes spurious zeros (scarsity) while preserving statistical characteristics of the data
- Can be integrated with any commercially available single cell sequencing technology, as an “add-on” kit
- Enables high resolution and high throughput characterisation of single cell data, unlocking the full potential of single cell experiments
The opportunity
Single-Cell RNA Sequencing (scRNA-Seq) technologies suffer from what is known as the ‘scarsity’ problem where lower expressed genes are underrepresented or not detected at all when compared to higher expressed genes. Scarsity means that the full transcriptome is never measured in single cells, which fundamentally limits the current applicability of scRNA-Seq to cell population identification.
Through weighting the transcriptomes, this simple two-step method can cost-effectively tackle the issue of scarsity. The method can be integrated with any commercially available single cell sequencing technology, as an “add-on” kit.
The method has been experimentally proven, showing that you can down-weight high expressing genes and up-weight low expressing genes while preserving data quality. The team plans to work on scaling up the number of genes and validating the method across different cell types. The final product will be an experimental kit similar to probe panels frequently used in applications such as exome-sequencing.
This method can enable high resolution and high throughput characterisation of single cell data, unlocking the full potential of single cell experiments.
Developed by Professor Florian Markowetz and Alexander Baker at the University of Cambridge.
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