Model spliced and unspliced mRNA dynamics to identify cell-state transitions in scRNA-seq data.
npx skills add https://github.com/Hung-3008/agusta --skill scvelo-hung-3008
Please help me install this Agent Skill. Skill: scvelo Source: https://github.com/Hung-3008/agusta/tree/main/.agents/skills/scvelo Command: npx skills add https://github.com/Hung-3008/agusta --skill scvelo-hung-3008
RNA velocity analysis to infer cell state transitions in single-cell RNA-seq data by modeling unspliced and spliced mRNA dynamics, enabling trajectory direction inference and developmental timing.
Run the complete RNA velocity workflow on an AnnData object containing spliced and unspliced layers to obtain velocity embeddings and latent time.
High-intent search queries and answers about installing and using this skill.
You infer cell trajectories by modeling spliced and unspliced mRNA dynamics using scVelo's dynamical or stochastic models. This workflow processes an AnnData object to estimate RNA velocity, construct a velocity graph, and compute latent time to reveal cell-state transitions.
RNA velocity is the measurement of transcription, splicing, and degradation rates by comparing unspliced and spliced mRNA levels. It estimates the rate of change in gene expression to predict the future state of individual cells, enabling trajectory inference and developmental timing.
Yes, the workflow seamlessly integrates with Scanpy's AnnData pipeline. It requires an AnnData object containing spliced and unspliced layers to perform preprocessing, velocity estimation, velocity graph construction, and downstream visualization.
You identify driver genes by applying fit_likelihood and velocity-based statistics during the dynamical modeling phase. This isolates key regulators that significantly influence cell-state transitions across the estimated latent time and trajectory.
Dynamical models solve the full equations of transcriptional dynamics to estimate reaction rates per gene, while stochastic models use moments of unspliced and spliced mRNA distributions. Both estimate RNA velocity but differ in their mathematical assumptions for trajectory inference.
Yes, the workflow is designed for scalable processing of large scRNA-seq datasets. It integrates with the Scanpy pipeline to handle large AnnData objects efficiently during velocity estimation, latent time computation, and velocity graph construction.
yf8578Perform RNA velocity analysis on single-cell RNA-seq AnnData objects.
LeonChaoXInfer RNA velocity and latent time from spliced and unspliced mRNA in AnnData.
dralkhAnalyze RNA velocity data from single-cell transcriptomic matrices with scVelo.
felixboehmPerform RNA velocity analysis on single-cell RNA-seq data with scVelo.
