Integrated Analysis of 10X Single Cell and Spatial Transcriptome

Integrated Analysis of 10X Single Cell and Spatial Transcriptome

Gene expression is temporally and spatially specific. scRNA-seq allows us to study transcriptome expression data at unprecedented resolutions. It can provide detailed transcriptional expression information of each cell and identify cell subtypes within the tissue, but it destroys the spatial composition of the source tissue in the necessary scRNA-seq tissue isolation step. Spatial transcriptomics (ST) can map transcriptional features to different tissue regions and provide complete information on the spatial location of tissues, but the information obtained cannot reach single-cell resolution. Therefore, scRNA-seq can be combined with spatial transcriptome sequencing technology, which can enable spatial localization of different single-cell subpopulations, cell type annotation of positional regions of the spatial transcriptome, and increase our understanding of specific cell subpopulations and their interactions in development, homeostasis, and disease.

CD Genomics offers an integrated 10x genomics scRNA-seq & spatial transcriptomics (ST) service to obtain single-cell spatio-temporal atlas data for spatio-temporal analysis of gene expression.

Single Cell and Spatial Transcriptome Expression Data Correlation Analysis

Pearson correlation analysis of gene expression data from scRNA-seq and spatial transcriptome of the same sample or different sections of the same sample to assess the similarity between technical replicates[1]

Integrated Analysis of 10X Single Cell and Spatial Transcriptome

Anchoring of Cell Types and Spatially Tissue Regions

Using the scRNA-seq dataset as a reference, factor analysis was used to predict the possible single-cell composition of each spot, thus enabling the spatial localization of all scRNA-seq subpopulations [2].

Integrated Analysis of 10X Single Cell and Spatial Transcriptome

Multimodal Interactive Analysis

To annotate the precise cellular composition of different tissue regions, a multimodal intersection analysis method [3] was introduced to integrate scRNA-seq data and ST data. The MIA method infers the enrichment of specific cell types in specific tissue regions by calculating the degree of overlap between differential genes in a region and cell-type differential genes identified by scRNA-seq data.

Integrated Analysis of 10X Single Cell and Spatial Transcriptome

CD Genomics has extensive experience in single-cell sequencing services and R&D, and has accumulated experience in 10x Genomics single-cell sequencing of more than 100 different tissue types.

10x Genomics Single Cell Sequencing

Single-cell transcriptome Sequencing

Single-cell Immune Repertoire Sequencing

Single-cell ATAC Sequencing

Single-cell ATAC+ Transcriptome Sequencing

Single-cell Whole Genome Bisulfite Sequencing

10x Genomics Spatial Transcriptome Sequencing

With the development of high-throughput sequencing technology, scRNA-seq & ST are increasingly applied to research in various fields. But how to realize the combination of scRNA-seq & ST to analyze and mine the data from a deeper level? How to interpret the biological significance of these data? If you are also interested in single cell and spatial transcription technology, please feel free to consult us!


  1. A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart
  2. Spatiotemporal analysis of human intestinal development at single-cell resolution
  3. Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma
For research use only, not intended for any clinical use.

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