ArticleNature biotechnology2025
Gene trajectory inference for single-cell data by optimal transport metrics.
Article in Nature biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.
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Who cites it
38 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Deciphering the biological underpinnings behind prognostic MRI-based imaging signatures in breast cancer: a systematic review.Journal of translational medicine · 2025Pooled it
- Single-cell meta-analysis of T cells reveals clonal dynamics of response to checkpoint immunotherapy.Cell genomics · 2025Pooled it
- Pseudotime uncovers restructuring dynamics and mitigators of metal catalyst deactivation.Science advances · 2026Article
- Learning stochastic dynamics and cell-fate landscapes from single-cell snapshots via optimal transport.Science advances · 2026Article
- Sharp cell type boundaries emerge from coordinated morphogen signaling.Genes & development · 2026Article
- DEAPLOG: Differential Expression Analysis and Pseudo-Temporal Locating and Ordering of Genes in Single-Cell Transcriptomic Data.Interdisciplinary sciences, computational life sciences · 2026Article
- Spatial and single-cell profiling identify NDRG1⁺ macrophages as key hallmark of angiogenic remodeling and platinum resistance in HGSOC.Translational oncology · 2026Article
- Hepatic Mechanisms and Therapeutic Target Underpinning Hypercoagulation in Obesity: Insights From Genetic and Transcriptomic Analyses.Exploration (Beijing, China) · 2026Article
- A single-cell atlas of porcine hematopoietic development.Nature communications · 2026Article
- SupeRJump: Determining normal and leukemic differentiation fate through semi-supervised jump diffusion modeling.bioRxiv : the preprint server for biology · 2026Article
- Foundation models in omics research: a comprehensive survey.Briefings in bioinformatics · 2026Review
- Self-supervised graph contrastive learning for scRNA-seq clustering.Journal of translational medicine · 2026Article
- Modeling development of tertiary lymphoid structures in pulmonary tuberculosis by 3D profiling and trajectory analysis.bioRxiv : the preprint server for biology · 2026Article
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- Dissecting the transcriptomic signature of porcine oocyte during primordial follicle formation from single cell resolution.Journal of ovarian research · 2026Article
- Quantitative coupling of clonal CNV evolution and spatially restricted malignant states identifies MFGE8 as a candidate late-state-associated target in breast cancer.Journal of translational medicine · 2026Article
- Identification of a new population of TnnBone research · 2026Article
- Locat: Joint enrichment and depletion testing identifies localized marker genes in single-cell transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Mucosal Inflammation Shapes Human Neutrophil States in Tissue and Circulation.bioRxiv : the preprint server for biology · 2026Article
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13 authors.
Funding
Abstract
Single-cell RNA sequencing has been widely used to investigate cell state transitions and gene dynamics of biological processes. Current strategies to infer the sequential dynamics of genes in a process typically rely on constructing cell pseudotime through cell trajectory inference. However, the presence of concurrent gene processes in the same group of cells and technical noise can obscure the true progression of the processes studied. To address this challenge, we present GeneTrajectory, an approach that identifies trajectories of genes rather than trajectories of cells. Specifically, optimal transport distances are calculated between gene distributions across the cell-cell graph to extract gene programs and define their gene pseudotemporal order. Here we demonstrate that GeneTrajectory accurately extracts progressive gene dynamics in myeloid lineage maturation. Moreover, we show that GeneTrajectory deconvolves key gene programs underlying mouse skin hair follicle dermal condensate differentiation that could not be resolved by cell trajectory approaches. GeneTrajectory facilitates the discovery of gene programs that control the changes and activities of biological processes.
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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.