Single-cell RNA sequencing (scRNA-seq)
Also known as: scRNA-seq · scRNA · single-cell RNA-seq · single-cell transcriptomics
Assay underlying most cell-state studies and atlases in the library, for example the Neftel study of 28 tumors and the GBmap atlas of more than one million cells. VC0059 VC0060 VC0063 VC0064
Review pending Version 0.1.0 · status: draft · last expert review: not yet reviewed
Relations
No typed relations recorded for this entity yet.
Appears in research topics
- Mesenchymal-like (MES-like) glioblastoma cell state (Cell states)
- Glioblastoma single-cell and spatial datasets (Datasets)
Appears in library items (17)
Items whose title, tags or one-line summary match this entity (derived from the data), plus the items cited as evidence for the description.
- VC0057 Assessing scale and predictive diversity in models for single-cell transcriptomics based on Geneformer. — Chen J, Schmidt F, Henao R., PLoS computational biology, 2026
- VC0132 Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations — Suter et al., Nature Communications, 2026
- VC0060 Charting the single-cell and spatial landscape of IDH-wild-type glioblastoma with GBmap. — Ruiz-Moreno C et al., Neuro-oncology, 2025
- VC0082 Single-cell analysis reveals a longitudinal trajectory of meningioma evolution and heterogeneity. — Lee JY, Lee EJ, Seo BY, Kim J, Song Y, Lee D, Moon N, Koo H, Park CK, Kim MS, Park SI, Nam DH, Kong DS, Sa JK., Nature communications, 2025
- VC0072 A method for in silico exploration of potential glioblastoma multiforme attractors using single-cell RNA sequencing. — Vieira Junior MG, de Almeida Côrtes AM, Gonçalves Carneiro FR, Carels N, Silva FABD., Scientific reports, 2024
- VC0011 Large-scale foundation model on single-cell transcriptomics. — Hao M, Gong J, Zeng X, Liu C, Guo Y, Cheng X, Wang T, Ma J, Zhang X, Song L., Nature methods, 2024
- VC0008 scGPT: toward building a foundation model for single-cell multi-omics using generative AI. — Cui H, Wang C, Maan H, Pang K, Luo F, Duan N, Wang B., Nature methods, 2024
- VC0087 Single-cell transcriptomic analyses provide insights into the cellular origins and drivers of brain metastasis from lung adenocarcinoma. — Wang Z, Wang Y, Chang M, Wang Y, Liu P, Wu J, Wang G, Tang X, Hui X, Liu P, Guo X, Xing B, Wang Y, Han Z, Ma W., Neuro-oncology, 2023
- VC0065 The landscape of tumor cell states and spatial organization in H3-K27M mutant diffuse midline glioma across age and location. — Liu I et al., Nature genetics, 2022
- VC0083 Single-cell profiling of human dura and meningioma reveals cellular meningeal landscape and insights into meningioma immune response. — Wang AZ et al., Genome medicine, 2022
- VC0030 · preprint scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data — Yang F, Wang W, Wang F, Fang Y, Tang D, Huang J, Lu H, Yao J., bioRxiv, 2021
- VC0068 Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. — Couturier CP et al., Nature communications, 2020
- VC0080 Single-Cell Transcriptomics in Medulloblastoma Reveals Tumor-Initiating Progenitors and Oncogenic Cascades during Tumorigenesis and Relapse. — Zhang L et al., Cancer cell, 2019
- VC0079 Resolving medulloblastoma cellular architecture by single-cell genomics. — Hovestadt V et al., Nature, 2019
- VC0059 An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma. — Neftel C et al., Cell, 2019
- VC0064 Developmental and oncogenic programs in H3K27M gliomas dissected by single-cell RNA-seq. — Filbin MG et al., Science (New York, N.Y.), 2018
- VC0063 Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq. — Venteicher AS et al., Science (New York, N.Y.), 2017
For research and education only. Not medical advice and not a recommendation of any diagnosis, treatment or product. Patients should consult their own physicians.