spatial transcriptomic profiles (10X Genomics)
86
Structured Review
10X Genomics
spatial transcriptomic profiles
Spatial Transcriptomic Profiles, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/spatial+transcriptomic+profiles/data+spatial+transcriptomic/pmc12921006-326-0-7
Average 86 stars, based on 1 article reviews
Spatial Transcriptomic Profiles, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/spatial+transcriptomic+profiles/data+spatial+transcriptomic/pmc12921006-326-0-7
Average 86 stars, based on 1 article reviews
spatial transcriptomic profiles - by Bioz Stars,
2026-09
86/100 stars
Images
1) Product Images from "Association of copy number alterations with the immune transcriptomic landscape in cancer"
Article Title: Association of copy number alterations with the immune transcriptomic landscape in cancer
Journal: NPJ Systems Biology and Applications
doi: 10.1038/s41540-026-00649-8
Figure Legend Snippet: A Overview of the 294,159 bulk transcriptomic profiles collected from the three datasets: GPL570 , ARCHS4, and TCGA. Consensus independent component analysis (c-ICA) was applied to each dataset to disentangle the bulk transcriptomic profiles into statistically independent transcriptional components (TCs). The TCs were then classified as CNA-TCs if they captured the effect of copy number alterations (CNA) based on the transcriptional adaptation to CNA profiling (TACNA). Additionally, TCs that capture immune-related processes using gene set enrichment analysis (GSEA) were defined as immune-TCs. B Heatmaps showing CNA regions captured by the CNA-TCs. Each column corresponds to a CNA-TC, with genes arranged in genomic order. For each CNA-TC, regions where many genes have high gene weights—indicating a CNA effect as determined by TACNA—are marked in red (see inset example). Only the red-marked regions, which represent the specific CNA effect captured by the corresponding CNA-TC, are shown. The CNA-TCs are sorted based on the position of the CNA region they capture. C Heatmap showing the z-value of GSEA for each immune-TC across all immune-related gene sets from Gene Ontology—Biological Process and REACTOME.
Techniques Used: Capture-C
Figure Legend Snippet: A Three examples of immune-TC activity across cell types are shown. Single-cell RNA sequencing included 114,253 cells from 181 patients with 13 different cancer types from the single-cell tumor immune atlas for precision oncology. The transcriptomic profile of each cell was projected onto the GPL570 immune-TCs. Cell annotation was based on the labels defined in the immune atlas. Box plot colors represent major cell type groups. The boxplot displays the median as the central line, with box hinges representing the second and third quartiles, whiskers extending by half the interquartile range, and outliers shown as individual dots. B Three examples of tumor spatial transcriptomic datasets from 10x Genomics Visium are shown. The transcriptomic profile of each spatial spot was projected onto the GPL570 CNA- and immune-TCs, and CNA burden was inferred. The spatial organization of the activity of three immune-TCs is shown for each tumor.
Techniques Used: Activity Assay, Single Cell, RNA Sequencing
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