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Fluent BioSciences and NanoCellect Announce Joint Collaboration to Improve Resolution of Single-cell RNA Sequencing Analysis of Rare Cell Populations

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Fluent BioSciences and NanoCellect Announce Joint Collaboration to Improve Resolution of Single-cell RNA Sequencing Analysis of Rare Cell Populations | Pharmtech Focus

Fluent BioSciences, a biotechnology company focused on making single-cell analysis simple and accessible to every researcher, and NanoCellect Biomedical, Inc., a leader in the development and manufacturing of innovative and affordable solutions for cell sorting, jointly announced a collaboration to improve resolution and efficiency of single-cell RNA sequencing (scRNA-seq) analysis of rare cell populations.

Single-cell researchers are increasingly requiring scalable, flexible and accessible workflow solutions, and the combination of cell sorting on the NanoCellect platform followed by scRNA-seq on a novel, instrument-free platform for scRNA-seq based on Pre-templated Instant Partitions (PIPseq™) from Fluent can be a highly efficient solution for a wide range of single cell applications across oncology, immunology and neuroscience.

“For single-cell sequencing to truly become mainstream researchers need benchtop solutions that fit their diverse experimental needs rather than compromising the science with complex, expensive, and inflexible platforms.” stated Sepehr Kiani Ph.D., co-founder, and CEO of Fluent BioSciences. “I am very pleased that Fluent and NanoCellect are able to leverage and combine the unique advantages of our respective technologies to expand the use of single-cell RNA sequencing for rare cell populations.”

“Reliable and reproducible sample preparation is critically important to the scRNAseq workflow” stated Jose Morachis, Ph.D., President and co-founder at NanoCellect.  “NanoCellect’s WOLF® and WOLF G2® Cell Sorters can function as a valuable step in the scRNA-seq workflow by isolating only cells of interest while removing dead cells and debris, thus improving scRNA-seq resolution of rare cell populations of interest and overall sequencing data quality.”

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