ArticleGenome biology2019
scPred: accurate supervised method for cell-type classification from single-cell RNA-seq data.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 265 papers, 1 of them a synthesis that pooled it.
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Who cites it
265 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Automated and reproducible cell identification in mass cytometry using neural networks.Briefings in bioinformatics · 2023Pooled it
- Medicinal cannabis plant extract (NTI164) modifies epigenetic, ribosomal, and immune pathways in paediatric acute-onset neuropsychiatric syndrome.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026Trial
- Leveraging Single-Cell RNA Sequencing to Characterize Murine Ewing Sarcoma Xenografts.Methods in molecular biology (Clifton, N.J.) · 2027Article
- TORC: Target-Oriented Reference Construction for Supervised Cell-Type Identification in scRNA-seq.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.European archives of psychiatry and clinical neuroscience · 2026Article
- scPlantAnnotate: an accurate and robust transformer-based model for plant cell type annotation.Journal of advanced research · 2026Article
- ScanNet: Single-cell annotation informed by transcriptional regulation Network via iterative heterogeneous graph learning.PLoS computational biology · 2026Article
- In Vitro Single-Cell Transcriptomic Profiling of Cultured Stem Cells From Apical Papilla and Dental Pulp Stem Cells: Unveiling Cellular Heterogeneity.International dental journal · 2026Article
- Multi-omic characterization of 14q deletion in renal clear cell carcinoma identifiesJournal for immunotherapy of cancer · 2026Article
- Brain endothelial cells orchestrate a neuroprotective antiviral state in the CNS in response to peripheral viral pattern sensing.Immunity · 2026Article
- scDifformer: diffusion-based post-training for virtual cell modeling across large-scale single-cell data.Nucleic acids research · 2026Article
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
- scMapNet: Marker-based cell type annotation of scRNA-seq data via vision transfer learning with tabular-to-image transformations.Journal of advanced research · 2026Article
- Interpretable deep generative ensemble learning for single-cell omics with Hydra.Molecular systems biology · 2026Article
- Hierarchical classification of immune cell transcriptomes at population-scale.bioRxiv : the preprint server for biology · 2026Article
- Classification of indeterminate and off-target cell types within human kidney organoid differentiation.iScience · 2026Article
- Natural killer cell-mediated immunosurveillance modulates liver cancer evolution through cancer stemness enhancement and lipid metabolism reprogramming.Nature communications · 2026Article
- MipSScs: Artificial neural network-based data integration of 2D/3D single-cell spatial RNA sequence data from virus-infected human cerebral organoids.bioRxiv : the preprint server for biology · 2026Article
- Computational modelling of cell identity.The Biochemical journal · 2026Review
- Article
205 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell RNA sequencing has enabled the characterization of highly specific cell types in many tissues, as well as both primary and stem cell-derived cell lines. An important facet of these studies is the ability to identify the transcriptional signatures that define a cell type or state. In theory, this information can be used to classify an individual cell based on its transcriptional profile. Here, we present scPred, a new generalizable method that is able to provide highly accurate classification of single cells, using a combination of unbiased feature selection from a reduced-dimension space, and machine-learning probability-based prediction method. We apply scPred to scRNA-seq data from pancreatic tissue, mononuclear cells, colorectal tumor biopsies, and circulating dendritic cells and show that scPred is able to classify individual cells with high accuracy. The generalized method is available at https://github.com/powellgenomicslab/scPred/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.