biostudies-literatureLan TAustralian Research Council Discovery Projecte122https://www.ebi.ac.uk/biostudies/studies/S-EPMC9757071biostudies-literatureUnknown50(21)Tree- and linear-shaped cell differentiation trajectories have been widely observed in developmental biologies and can be also inferred through computational methods from single-cell RNA-sequencing datasets. However, trajectories with complicated topologies such as loops, disparate lineages and bifurcating hierarchy remain difficult to infer accurately. Here, we introduce a density-based trajectory inference method capable of constructing diverse shapes of topological patterns including the most intriguing bifurcations. The novelty of our method is a step to exploit overlapping probability distributions to identify transition states of cells for determining connectability between cell clusters, and another step to infer a stable trajectory through a base-topology guided iterative fitting. Nucleic acids researchDensity-based detection of cell transition states to construct disparate and bifurcating trajectories.PMC9757071DP180100120Hutvagner GLan TLi JZhang XWong LLiu TfalseDensity-based detection of cell transition states to construct disparate and bifurcating trajectories.Tree- and linear-shaped cell differentiation trajectories have been widely observed in developmental biologies and can be also inferred through computational methods from single-cell RNA-sequencing datasets. However, trajectories with complicated topologies such as loops, disparate lineages and bifurcating hierarchy remain difficult to infer accurately. Here, we introduce a density-based trajectory inference method capable of constructing diverse shapes of topological patterns including the most intriguing bifurcations. The novelty of our method is a step to exploit overlapping probability distributions to identify transition states of cells for determining connectability between cell clusters, and another step to infer a stable trajectory through a base-topology guided iterative fitting. 2022-01-01T00:00:00Z2022 Nov2026-05-31T11:03:04.354Z2025-04-19T10:46:54.938ZS-EPMC97570713612466510.1093/nar/gkac785