RNA velocity is based on bridging measurements to an underlying mechanism, mRNA splicing, with two modes indicating the current and future state.
MultiVelo uses a probabilistic latent variable model to estimate the switch time and rate parameters of chromatin accessibility and gene expression .
[6] DeepVelo is a neural network–based ordinary differential equation that can model complex transcriptome dynamics by describing continuous-time gene expression changes within individual cells.
DeepVelo has been applied to public datasets from different sequencing platforms to (i) formulate transcriptome dynamics on different time scales, (ii) measure the instability of cell states, and (iii) identify developmental driver genes via perturbation analysis.
[7] UnitVelo is a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities.