Project description:This submission is a dataset of two modalities, single-nucleus transcriptomics and single-nuclei spatial transcriptomics in the spinal cords of mice. The single-nuclei transcriptomics data is harvested and profiled using 10x Genomics Chromium Single Cell Kit Version. The single-nuclei spatial transcriptomics data is harvested and profiled using Visium Spatial Gene Expression.
Project description:These data were used in the spatial transcriptomics analysis of the article titled \\"Single-Cell and Spatial Transcriptomics Analysis of Human Adrenal Aging\\".
Project description:Skeletal muscles are complex organs consisting of multiple tissues, including connective tissue, blood vessels, nerves and multinucleated myofibers. Single-nucleus transcriptomics analyses have revealed distinctive myonuclear populations related to myofiber type and to specialized regions, including neuromuscular and myotendinous junctions. However, the use of tissue dissociation methods prevented access to global spatial organization. Here we applied RNA tomography (TOMOseq), a spatial transcriptomics approach, to explore gene expression differences along murine tibialis anterior muscles.
Project description:Identification of cell types in the interphase between muscle and tendon by Visium Spatial Transcriptomics of four human semitendinous muscle-tendon biopsies. Cell types identified by single nuclei RNA seq on similar tissue were localized in situ with the use of Spatial Transcriptomics.
Project description:We profiled 87 primary-recurrentpatient-matched paired GBM specimens with single-nucleus RNA and bulk-DNA sequencing and single-cell open-chromatin and spatial transcriptomics/proteomics assays. We found that recurrent GBMs are characterized by a shift to a mesenchymal phenotype in response to therapy
Project description:We generated a comprehensive dataset utilizing the cuprizone model. This dataset encompasses bulk RNA-seq, single-nucleus RNA-seq (snRNA-seq), and spatial transcriptomics, with the aim of investigating the molecular changes linked to the cuprizone-induced demyelination phenotype. Integration of these omics dataset allowed us to investigate the changes occurring at both the single-cell and spatial levels, thereby enabling a deeper understanding of the cellular dynamics and molecular interactions associated with the cuprizone-induced demyelination phenotype.
Project description:We generated a comprehensive dataset utilizing the cuprizone model. This dataset encompasses bulk RNA-seq, single-nucleus RNA-seq (snRNA-seq), and spatial transcriptomics, with the aim of investigating the molecular changes linked to the cuprizone-induced demyelination phenotype. Integration of these omics dataset allowed us to investigate the changes occurring at both the single-cell and spatial levels, thereby enabling a deeper understanding of the cellular dynamics and molecular interactions associated with the cuprizone-induced demyelination phenotype.
Project description:We generated a comprehensive dataset utilizing the cuprizone model. This dataset encompasses bulk RNA-seq, single-nucleus RNA-seq (snRNA-seq), and spatial transcriptomics, with the aim of investigating the molecular changes linked to the cuprizone-induced demyelination phenotype. Integration of these omics dataset allowed us to investigate the changes occurring at both the single-cell and spatial levels, thereby enabling a deeper understanding of the cellular dynamics and molecular interactions associated with the cuprizone-induced demyelination phenotype.
Project description:Comparison of single cell RNAseq and single nucleus RNAseq on four healthy human liver caudate lobes, with cell-types validated using one slice of a fifth healthy human for VISIUM Spatial Transcriptomics. Raw UMI count tables can be found here: https://figshare.com/projects/Human_Liver_SC_vs_SN_paper/98981 Processed Seurat Objects can be found here: https://www.dropbox.com/sh/sso15ehqmrrh6mk/AACKHOsSlZW0_Zy9cbCkOmMfa?dl=0
