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Single Cell Sequencing can reveal cell-to-cell differences and cellular heterogeneities that have been completely obscured by bulk RNA-seq, thus enabling a high-resolution exploration of the function of individual cells. Single-cell sequencing has a wide range of applications across biology and medicine, offering unprecedented insights into cellular behavior and function.
Based on the 10x Genomics® Chromium™ X technology, Parse Evercode™ Technology and Illumina® NovaSeq™ X Plus platform, Novogene from an expertise perspective offers comprehensive single cell sequencing solutions from sample processing, library preparation, sequencing to bioinformatic analysis at a cost-effective, competitive price and in a customer-focused manner, allowing you to explore the transcriptome and immune profiling cell-by-cell in the sea of cells.
Application of 10x Single-cell Gene Expression in Oncology Research
Single-cell sequencing is an emerging technique of high-throughput sequencing and analyzing genomics, transcriptome, and epigenomics at single-cell level. The development of sequencing technology provides fertile ground, making it a popular research field in life sciences and it is also more widely used in basic medicine, clinical translation research and Oncology. Oncology is a specialized field within medicine dedicated to the comprehensive study, diagnosis, treatment, and prevention of cancer. The cutting-edge scRNA-seq technique enables researchers to dissect the heterogeneity within tumor tissues, providing insights into the diverse cell populations, their interactions, and the molecular mechanisms underlying cancer progression.
Application of 10x Single-cell Gene Expression in Immunology Research
Single-cell sequencing is an emerging technique of high-throughput sequencing and analyzing genomics, transcriptome, and epigenomics at the single-cell level. Since the advent of single-cell transcriptome sequencing in 2009, diverse methodologies have been developed. These recent advances in single-cell techniques have provided a way to investigate complex biological questions without any prior information. The immune system is one such mysterious system, with a network of cells that function in various pathophysiological pathways. With the help of the 10x Genomics single-cell platform, it is now possible to study this complexity.
Application of 10x Single-cell Gene Expression in Neuroscience Research
The human brain comprises billions of diverse cell types intricately interconnected to form complex neural circuits. The cutting-edge scRNA-seq technique enables researchers to delve into individual brain cells’ molecular landscapes, unlocking new insights into neural development, function, and dysfunction. scRNA-seq allows for the identification and characterization of rare cell populations that bulk methods may overlook. Download our ebook to explore detailed applications and recommended experimental design outlines, curated by our expert team.
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*Contact us for species-specific recommendations and tissue type guidance.
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**Sample type preferences may vary based on sequencing requirements and sample compatibility.
From sample preparation, library preparation, sequencing and data quality control, to bioinformatics analysis, Novogene provides high-quality products and professional services. Each step is performed in agreement with a high scientific standard and meticulous design to ensure high-quality research results.
Dysregulation of brain and choroid plexus cell types in severe COVID-19
Yang, A.C., Kern, F., Losada, P.M. et al. Dysregulation of brain and choroid plexus cell types in severe COVID-19. Nature 595, 565–571 (2021). https://doi.org/10.1038/s41586-021-03710-0
GD2-CAR T cell therapy for H3K27M-mutated diffuse midline gliomas
Majzner, R.G., Ramakrishna, S., Yeom, K.W. et al. GD2-CAR T cell therapy for H3K27M-mutated diffuse midline gliomas. Nature 603, 934–941 (2022). https://doi.org/10.1038/s41586-022-04489-4
Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection
Wang, H., Liu, C., Xie, X., Niu, M., Wang, Y., Cheng, X., Zhang, B., Zhang, D., Liu, M., Sun, R., Ma, Y., Ma, S., Wang, H., Zhu, G., Lu, Y., Huang, B., Su, P., Chen, X., Zhao, J., Wang, H., … Cheng, T. (2023). Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection. Immunity, 56(6), 1410–1428.e8. https://doi.org/10.1016/j.immuni.2023.05.007
Figure 1 The t-SNE and UMAP plots
Note:Each point represents a cell, and each color designates a cluster. For visualization purposes, dimensionality was further reduced to 2D using t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). Both of them try to find a low-dimensional representation that preserves relationships between neighbors in high-dimensional space. Compared to t-SNE, the UMAP visualization tends to have more compact visual clusters with more empty spaces between them.
Figure 2 Expression Pattern of Marker Genes
Note: Darker red represents a higher expression level, and darker blue dictates a lower expression level. Heatmaps show the expression of indicated marker genes for given cells and features. In this case, we plotted the top 10 markers (or all markers if less than 10) for each cluster.
Figure 3 Expression Level of Marker Genes
Note: The X-axis represents the cluster, and the Y-axis represents the expression level. Violin plots show the relative expression levels of marker genes among all clusters. (Only six marker genes are shown here)
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