Storm: Incorporating transient stochastic dynamics to infer the RNA velocity with metabolic labeling information
Fig 2
Stochastic model combined with steady-state assumptions for one-shot data without splicing information.
Storm in this figure refers to the inference strategy of CSP-Baseline model combined with the steady state assumption. A. Streamline projected in the UMAP space plots of primary human HSPCs datasets from scNT-seq [26]. B. Degradation rates γt estimated with steady-based method in Storm compared to that of the Dynamo method in the primary human HSPCs datasets. C. Streamline projected in the UMAP space plots of neuronal activity under KCl polarization datasets from scNT-seq [18]. D. Same as B., but for the neuronal activity datasets. E. Streamline plots of the sci-fate dataset [19] reveal two orthogonal processes of GR response and cell-cycle progression. From left to right: streamline plot on the first two PCs, the second two PCs, and the first two UMAP components that are reduced from the four PCs, respectively. The first row is the result of Storm and the second row is the result of Dynamo. F. Streamline projected in the UMAP space plots of the dataset from PerturbSci-Kinetics [22].