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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.
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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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