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Single Cell Transcriptomics Services

Single-cell sequencing, a recently developed and potent technique, is the ideal method for resolving cellular networks. It provides systematic insights into the resolution of cellular-level life mechanisms by simultaneously detecting tens of thousands of cells, mapping the cellular atlas of tissues or organs, and elucidating the regulatory patterns and state changes among cells. Single-cell transcriptome sequencing, spatial transcriptome sequencing, single-cell ATAC sequencing, and single-cell immunome reveal tissue-level heterogeneity as scientific research continues to advance.

A growing number of scientists have recently focused on single nuclei RNA sequencing (snRNA-seq). In contrast to scRNA-seq, which sequences individual cells, snRNA-seq prepares, sequences, and analyzes single-cell nuclear suspensions.

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Single cell RNA sequencing Service

Single cell RNA sequencing (scRNA-seq), a recent development in biology, offers sequence details for individual cells and demonstrates their individuality. Understanding the function of a single cell allows scRNA-seq to answer issues that bulk analysis is unable to.
Single cells can provide information about the transcriptome. In order to fully capture the heterogeneity of a sample in tens of thousands of cells, we establish a high throughput platform. Regarding scRNA-seq research, Creative Biolabs is dedicated to effectiveness, confidentiality, and quick, accurate service.

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Single nuclei RNA sequencing Service

Single nuclei RNA sequencing (snRNA-seq) is an RNA sequencing technique used to profile difficult-to-isolate cells, such as those from archived tissues or those that are hard to dissociate. snRNA-seq techniques reduce dissociation bias, sample compatibility, and transcriptional stress responses induced by dissociation.
Creative Biolabs provides a comprehensive range of customized, high-quality services in single cell nuclei RNA sequencing to support scientific research in related biomedical industries worldwide, as well as a single-cell level research application platform for complex tissues such as brain tissue, heart, kidney, or some rare, cryopreserved samples, facilitating the investigation of tumor cell heterogeneity and pathological mechanisms.

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Creative Biolabs provides single cell RNA sequencing and single nuclei RNA sequencing services in order to fully capture the heterogeneity of a sample. For any information, please contact us.

Published Data

Paper Title Systematic comparison of single-cell and single-nucleus RNA-sequencing methods
Journal Nature Biotechnology
Published 2020
Abstract Single-cell transcriptomics has revolutionized our capacity to characterize cell states, but profound biological comprehension requires more than a taxonomic listing of clusters. As new methods emerge to measure distinct cellular modalities, integrating these datasets to better comprehend cellular identity and function represents a significant analytical challenge. Here, the authors develop a strategy to "anchor" disparate datasets together, allowing us to integrate single cell measurements not only across scRNA-seq technologies but also across modalities. They anchor scRNA-seq experiments with scATAC-seq to investigate chromatin differences in closely related interneuron subsets and map protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Finally, they harmonize in-situ gene expression and scRNA-seq datasets to enable transcriptome-wide imputation of spatial gene expression patterns. Their work presents a strategy for the assembly of standardized references and the transfer of data between datasets.
Result Result Using mouse cortex as an example, they performed single cell RNA-seq with 10x Chromium (v2), Smart-seq2, and sci-RNA-seq, as well as single nuclei RNA-seq with the DroNc-seq method. Compared to the results of the aforementioned methods, they discovered that the mouse cortex contains distinct cell types, not limited to excitatory and inhibitory neurons, such as astrocytes, oligodendrocytes, oligodendrocyte progenitor cells, microglia, endothelial cells, and pericytes. All of these cell types were identified in both experiments for all methods except sci-RNA-seq, with the exception of pericytes, a rare cell type identified only in DroNc-seq Cortex1. Also missing from the sci-RNA-seq datasets were oligodendrocyte progenitor cells and microglia. In the AUC (area under the receiver operating characteristic curve) analysis, Smart-seq2, 10x Chromium (v2), and DroNc-seq all had high AUCs, but their relative ability to detect expected cells differed by cell type. Notably, the small number of cells contained in the Smart-seq2 datasets was sufficient for these cell types.

Fig.3 Cell type identification and assignment in cortex nuclei. (Hu, 2016)Fig.3 Cell type identification and assignment in cortex nuclei1.


  1. Ding, Jiarui, et al. "Systematic comparison of single-cell and single-nucleus RNA-sequencing methods." Nature biotechnology 38.6 (2020): 737-746.
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