Velde: constructing cell potential landscapes by RNA velocity vector field decomposition

TL;DR

This paper introduces a novel method to construct combined cell differentiation and cell cycle potential landscapes from single-cell RNA sequencing data using Helmholtz-Hodge decomposition of RNA velocity vector fields.

Contribution

It presents the natural Helmholtz-Hodge decomposition to separate RNA velocity fields into components representing differentiation and cell cycle, enabling simultaneous landscape construction.

Findings

Successfully applied to synthetic datasets

Effectively analyzed real single-cell RNA data

Provides detailed visualization of cell development processes

Abstract

The Waddington landscape serves as a metaphor illustrating the developmental process of cells, likening it to a small ball rolling down various trajectories into valleys. Constructing an epigenetic landscape of this nature aids in visualizing and gaining insights into cell differentiation. Development encompasses intricate processes involving both cell differentiation and cell cycles. However, current landscape methods solely focus on constructing a potential landscape for cell differentiation, neglecting the accompanying cell cycle. This paper introduces a novel method that simultaneously constructs two types of potential landscapes using single-cell RNA sequencing data. Specifically, it presents the natural Helmholtz-Hodge decomposition (nHHD) of a continuous vector field within a bounded domain in n-dimensional Euclidean space. This decomposition uniquely breaks down the vector field into a gradient field, a rotation field, and a harmonic field. Utilizing this approach, the RNA velocity vector field is separated into a curl-free component representing cell differentiation and a curl component representing the cell cycle. By calculating the corresponding potential functions, potential landscapes for both cell differentiation and the cell cycle are obtained. Finally, the efficacy of this method is demonstrated through its application to synthetic and real datasets.