10X Genomics has released data from a study of Chromium Single Cell 3' Solution which is the company’s single-cell RNA-sequencing technology to provide single cell data sets.

This new technology has been designed to provide single-cell expression measurements, enabling the discovery of gene expression dynamics and molecular profiling of individual cell types at scale.

The study, titled 'Massively parallel digital transcriptional profiling of single cells', was co-authored by researchers from the Fred Hutchinson Cancer Research Center.

"Results indicated superior scalability and robustness of this system for single cell RNA-sequencing."

Fred Hutchinson Cancer Research Center co-author and principal investigator Jason Bielas said: “Earlier methods for single-cell RNA-sequencing posed practical challenges for many labs, including our own.

“Therefore, we welcomed the opportunity to collaborate with 10x Genomics to help validate and tailor its single-cell RNA-sequencing platform to unlock the potential of single-cell transcriptomics in both biological and clinical research.”

The researchers collected transcriptome data from approximately 250,000 single cells across 29 samples to show the technical performance and applications of the Chromium Single Cell 3’ Solution.

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Results indicated superior scalability and robustness of this system for single cell RNA-sequencing, with comparable sensitivity to existing methods.

The system’s rapid cell encapsulation and high cell capture efficiency enabled analysis of clinical samples from patients with acute myeloid leukemia.

With the use of the Chromium Single Cell 3’ Solution, researchers determined host and donor chimerism at single cell resolution and compared immune cell subpopulation changes in patients before and after transplant.

The company claimed that existing methods for single-cell RNA-sequencing face practical challenges when scaling to tens of thousands or more cells in throughput. The commercially available Chromium Single Cell 3’ Solution allows single cell RNA-sequencing at scale, with high cell capture efficiency and flexible throughput.