ArticleBMC bioinformatics2022
Detection of cell markers from single cell RNA-seq with sc2marker.
Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
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- Identification of distinct cDC2 subpopulations that direct microbiota-specific T cell differentiation.bioRxiv : the preprint server for biology · 2025Article
- Distinct stromal cell populations define the B-cell acute lymphoblastic leukemia microenvironment.Leukemia · 2025Article
- Batch correction methods used in single-cell RNA sequencing analyses are often poorly calibrated.Genome research · 2025Article
- The neuronal and glial cell diversity in the celiac ganglion revealed by single-nucleus RNA sequencing.Scientific reports · 2025Article
- Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations.NPJ systems biology and applications · 2024Article
- A single-cell transcriptomic dataset of pluripotent stem cell-derived astrocytes via NFIB/SOX9 overexpression.Scientific data · 2024Article
- Hofbauer cells and fetal brain microglia share transcriptional profiles and responses to maternal diet-induced obesity.Cell reports · 2024Article
- Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations.bioRxiv : the preprint server for biology · 2024Article
- Hofbauer cells and fetal brain microglia share transcriptional profiles and responses to maternal diet-induced obesity.bioRxiv : the preprint server for biology · 2023Article
- Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets.Genome biology · 2023Review
- CellBRF: a feature selection method for single-cell clustering using cell balance and random forest.Bioinformatics (Oxford, England) · 2023Article
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4 authors.
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Abstract
backgroundSingle-cell RNA sequencing (scRNA-seq) allows the detection of rare cell types in complex tissues. The detection of markers for rare cell types is useful for further biological analysis of, for example, flow cytometry and imaging data sets for either physical isolation or spatial characterization of these cells. However, only a few computational approaches consider the problem of selecting specific marker genes from scRNA-seq data.
resultsHere, we propose sc2marker, which is based on the maximum margin index and a database of proteins with antibodies, to select markers for flow cytometry or imaging. We evaluated the performances of sc2marker and competing methods in ranking known markers in scRNA-seq data of immune and stromal cells. The results showed that sc2marker performed better than the competing methods in accuracy, while having a competitive running time.
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