SingleR
Matrix file
Click to select or drag file here.
Cell label file
Click to select or drag file here.
Dataset
Tissue section
Introduction
To observe how user cell tags were distributed within the spatial transcriptome data, we utilized singleR to map user cell tags back to the spatial transcriptome. Although spatially resolved transcriptomics technologies, such as ST and Visium, have revealed fine-scale cellular spatial in diverse tissue types and diseases. The primary technological limitation of ST and Visium is the lack of single-cell resolution and the ability to capture 5–10 cells per spot, which means that for the majority of tissue cells, it is more likely that the same type of cells are dispersed throughout the same area.
Count Matrix
Cell Annotation
Reference
Spatial transcriptome
Embedding png
Label distribution
Important note
Please ensure that the gene name of the submission matrix is the same as the gene of the spatial transcriptome.
File size: a maximum of 50 Mb
File extension: tsv, csv or gz
Matrix file: File format: (column should be separated by tab), different rows correspond to different genes; different columns correspond to different cells.
Cell label file: The first column is cells and the second column is annotations.