ArticleGenome biology2020
Accounting for cell type hierarchy in evaluating single cell RNA-seq clustering.
Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- scMustree: a multi-scale functional hierarchy for single-cell transcriptomic analysis.Bioinformatics (Oxford, England) · 2026Article
- SpaHNR: a spatial domain identification method via sparse attention-based hierarchical node representation and multi-view contrastive learning.BMC bioinformatics · 2026Article
- HIDF: Integrating Tree-Structured scRNA-seq Heterogeneity for Hierarchical Deconvolution of Spatial Transcriptomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- On metrics for subpopulation detection in single-cell and spatial omics data.Nucleic acids research · 2025Article
- CeiTEA: Adaptive Hierarchy of Single Cells with Topological Entropy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Article
- Spectral divergence prioritizes key classes, genes, and pathways shared between substance use disorders and cardiovascular disease.Frontiers in neuroscience · 2025Article
- Identifying T-cell clubs by embracing the local harmony between TCR and gene expressions.Molecular systems biology · 2024Article
- CellMarkerPipe: cell marker identification and evaluation pipeline in single cell transcriptomes.Scientific reports · 2024Article
- ACCURATE ESTIMATION OF RARE CELL-TYPE FRACTIONS FROM TISSUE OMICS DATA VIA HIERARCHICAL DECONVOLUTION.The annals of applied statistics · 2024Article
- Principled and interpretable alignability testing and integration of single-cell data.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Uncertainty-aware single-cell annotation with a hierarchical reject option.Bioinformatics (Oxford, England) · 2024Article
- cellMarkerPipe: Cell Marker Identification and Evaluation Pipeline in Single Cell Transcriptomes.Research square · 2024Article
- scAce: an adaptive embedding and clustering method for single-cell gene expression data.Bioinformatics (Oxford, England) · 2023Article
- deCS: A Tool for Systematic Cell Type Annotations of Single-cell RNA Sequencing Data among Human Tissues.Genomics, proteomics & bioinformatics · 2023Article
- Review
- CeDAR: incorporating cell type hierarchy improves cell type-specific differential analyses in bulk omics data.Genome biology · 2023Article
- Incorporating cell hierarchy to decipher the functional diversity of single cells.Nucleic acids research · 2023Article
- A neural network-based method for exhaustive cell label assignment using single cell RNA-seq data.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Cell clustering is one of the most common routines in single cell RNA-seq data analyses, for which a number of specialized methods are available. The evaluation of these methods ignores an important biological characteristic that the structure for a population of cells is hierarchical, which could result in misleading evaluation results. In this work, we develop two new metrics that take into account the hierarchical structure of cell types. We illustrate the application of the new metrics in constructed examples as well as several real single cell datasets and show that they provide more biologically plausible results.
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