Dynamic Model

🧬 Dynamic RNA velocity model-- (8) effective scVelo analysis
🧬 Dynamic RNA velocity model-- (8) effective scVelo analysis

Here reveals biologically significant tumor development trajectory from real-world scRNAseq dataset by tweaking the key steps and parameters in scVelo pipeline to align with the math foundations of dynamic RNA velocity model and to improve the estimation accuracy.

May 28, 2025

🧬 Dynamic RNA velocity model-- (7) Gillespie Stochastic Simulation Algorithm
🧬 Dynamic RNA velocity model-- (7) Gillespie Stochastic Simulation Algorithm

Here delves into the Gillespie Stochastic Simulation Algorithm to generate high-quality simulated data with known ground truth. The simulation rigorously validate the adjustments of key (hyper)parameters and processing steps in scVelo for more accurate and meaningful analysis.

May 28, 2025

🧬 Dynamic RNA velocity model-- (6) computational handling in implementation
🧬 Dynamic RNA velocity model-- (6) computational handling in implementation

Here begins the deep dive into scVelo’s computational handling that is only unveiled in its implementation but reshapes visualization and interpretation. We look into neighbor reliance, seed dependency and object structure of scVelo in this sixth blog on effectively applying the dynamic model of RNA velocity.

May 28, 2025

🧬 Dynamic RNA velocity model-- (5) global time normalization
🧬 Dynamic RNA velocity model-- (5) global time normalization

scVelo source codes shows a ad-hoc voting method to calculate a global latent time, which was identified as key weaknees. Here present alternative methods to potentially address the relative scale of different genes and avoid the assumption of equal full cycle time for all genes.

May 28, 2025

🧬 Dynamic RNA velocity model-- (3) post hoc velocity graph
🧬 Dynamic RNA velocity model-- (3) post hoc velocity graph

In this third blog on effectively applying the dynamic model of RNA velocity, we look into post hoc computed cosine similarity and the exponential kernel that shape the RNA velocity graph and embedding. This begins our deep dive into scVelo’s post hoc computations that determine visualization and interpretation.

May 28, 2025

🧬 Dynamic RNA velocity model-- (2) parameter inference
🧬 Dynamic RNA velocity model-- (2) parameter inference

Here derives the mathematics underpinning the parameter inference of dynamic RNA velocity model, which is the second installment of our blog series to effectively apply the dynamic model in revealing the RNA velocity of single-cell RNAseq.

May 28, 2025

🧬 Dynamic RNA velocity model-- (1) math solutions
🧬 Dynamic RNA velocity model-- (1) math solutions

Here we delve into the mathematical foundations of the dynamic model of RNA velocity. This is the 1st installment of our blog series to clearly understand strengths and limitations of the dynamic model that is required for its effective application.

May 28, 2025