ArticleNature methods2024
Quantifying cell-state densities in single-cell phenotypic landscapes using Mellon.
Article in Nature methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- SupeRJump: Determining normal and leukemic differentiation fate through semi-supervised jump diffusion modeling.bioRxiv : the preprint server for biology · 2026Article
- IntegrateRigor: annotation-free integration optimization for cell identity recovery reveals cancer-immune interface niches.bioRxiv : the preprint server for biology · 2026Article
- Echo characterizes the desynchronization of gene expression and chromatin accessibility during cell-state transitions.bioRxiv : the preprint server for biology · 2026Article
- Single-cell trajectory inference for detecting transient events in biological processes.Nucleic acids research · 2026Article
- SCOPE: Localizing fate-decision states and their regulatory drivers in single-cell differentiation.bioRxiv : the preprint server for biology · 2026Article
- Transcriptomic Plasticity Is a Hallmark of Metastatic Pancreatic Cancer.Cancer research · 2026Article
- iAODE for benchmarking and continuum modeling of single-cell chromatin accessibility.Communications biology · 2026Article
- Sequential RNA polymerase II activation drives human hematopoiesis.Cell reports · 2026Article
- Innate Immune-Cloaked Microgel-Coated Mesenchymal Stromal Cells Reverse Persistent Pulmonary Fibrosis via Reparative Macrophages.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Distinct populations of lung capillary endothelial cells and their functional significance.Communications biology · 2025Article
- A transcriptomic atlas of astrocyte heterogeneity across space and time in mouse and marmoset.Neuron · 2025Article
- Single-Cell Transcriptome Profiling Reveals Conserved IFNγ-IL8 Signaling-Induced Antibacterial Neutrophil States during Bacterial Infection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Comparison of single-cell long-read and short-read transcriptome sequencing via cDNA molecule matching: quality evaluation of the MAS-ISO-seq approach.NAR genomics and bioinformatics · 2025Article
- Inferring causal trajectories from spatial transcriptomics using CASCAT.Nucleic acids research · 2025Article
- Patterns of intra- and intertumor phenotypic heterogeneity in lethal prostate cancer.The Journal of clinical investigation · 2025Article
- Joint representation and visualization of derailed cell states with Decipher.Genome biology · 2025Article
- Comparing phenotypic manifolds with Kompot: Detecting differential abundance and gene expression at single-cell resolution.bioRxiv : the preprint server for biology · 2025Article
- Extended culture of 2D gastruloids to model human mesoderm development.Nature methods · 2025Article
- Astrocyte regional specialization is shaped by postnatal development.bioRxiv : the preprint server for biology · 2025Article
- Computing hematopoiesis plasticity in response to genetic mutations and environmental stimulations.Life science alliance · 2025Article
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Abstract
Cell-state density characterizes the distribution of cells along phenotypic landscapes and is crucial for unraveling the mechanisms that drive diverse biological processes. Here, we present Mellon, an algorithm for estimation of cell-state densities from high-dimensional representations of single-cell data. We demonstrate Mellon's efficacy by dissecting the density landscape of differentiating systems, revealing a consistent pattern of high-density regions corresponding to major cell types intertwined with low-density, rare transitory states. We present evidence implicating enhancer priming and the activation of master regulators in emergence of these transitory states. Mellon offers the flexibility to perform temporal interpolation of time-series data, providing a detailed view of cell-state dynamics during developmental processes. Mellon facilitates density estimation across various single-cell data modalities, scaling linearly with the number of cells. Our work underscores the importance of cell-state density in understanding the differentiation processes, and the potential of Mellon to provide insights into mechanisms guiding biological trajectories.
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