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Single-cell RNA sequencing measures gene expression one cell at a time, revealing the cell types inside a tumour that bulk sequencing averages away.
Single-cell transcriptomics is the quantification and analysis of the transcriptomes of individual cells, which makes it possible to unravel heterogeneous cell populations, reconstruct developmental pathways and model transcriptional dynamics (Wikipedia). Droplet platforms such as 10x Genomics Chromium capture thousands of cells per run; CELLxGENE and the Human Cell Atlas hold tens of millions of profiled cells and are the training data for single-cell foundation models. Pseudobulk, summing the cells of a sample, recovers a bulk-like profile for comparison. Single-cell data is sparse and normalised differently from bulk, so a model trained on one is out of distribution on the other.
Showing the technology this term belongs to: Single-cell & spatial profiling.
Shares Single-cell and transcriptome foundation models: UCE, GeneCompass, BulkFormer, BulkRNABert, Foundation model, Cancer AI vocabulary (CanSim terms map) and the tag cansim-terms.
Shares AnnData and h5ad files, Cancer AI vocabulary (CanSim terms map) and the tag cansim-terms.
Shares Uberon anatomy ontology and the Cell Ontology, Cancer AI vocabulary (CanSim terms map) and the tag cansim-terms.
Shares Uberon anatomy ontology and the Cell Ontology, Cancer AI vocabulary (CanSim terms map) and the tag cansim-terms.
Shares Bulk RNA sequencing (RNA-seq) and the full transcriptome, Cancer AI vocabulary (CanSim terms map) and the tag cansim-terms.
Shares Bulk RNA sequencing (RNA-seq) and the full transcriptome, Cancer AI vocabulary (CanSim terms map) and the tag cansim-terms.
Shares Bulk RNA sequencing (RNA-seq) and the full transcriptome, Cancer AI vocabulary (CanSim terms map) and the tag cansim-terms.
Shares Virtual cell models and in-silico perturbation screens, Cancer AI vocabulary (CanSim terms map) and the tag cansim-terms.