WF-Velo: A New Method for RNA Velocity Analysis Based on Single-Cell Data

The direction of cell differentiation is very important to study the process of cell differentiation. There was a strong hypothesis that the direction was fixed in previous studies until the RNA velocity method appearance. It is a powerful tool to analyze cell differentiation. However, there is still some problem of it due to the low expression of unspliced mRNA readings and high randomness. This paper intends to propose a new method called WF-velo which means the whole feature (WF) are used during the process of RNA velocity estimations, while the part feature was used by the traditional method, to overcome the problem of the existed methods. By using the characteristics of the gene in the whole transcription process, the RNA velocity of cells can be estimated more realistically, and the cell differentiation process is more in line with biological phenomena compared with the cellDancer, scvelo, Deepvelo and other RNA velocity estimation algorithms. The pancreatic endocrine development dataset and the mouse hippocampus development dataset are tested by WF-velo. The cell differentiation trajectory shows that it is a good method to estimate the RNA velocity.