OmicFate, an algorithm for predicting fate factors from cell state density and pseudotime regression weights. , please read our paper: OmicFate: Unraveling the Secrets of Cellular Fate Determination

1 Introduction

Cellular pseudotime-related factors characterize participants in the temporal process of the cellular differentiation spectrum, and early regulators are essential for revealing the dynamic regulatory processes of cellular differentiation. Here, we present the histological fate factor prediction algorithm OmicFate, an algorithm for predicting fate factors from cell state density and pseudotime regression weights. We demonstrate the validity of OmicFate by dissecting genes, cellular interactions, and pathways in the early developmental spectrum, and we present evidence that addresses the temporal preference of the traditional pseudotime-related factor, emphasizing the importance of continuous processes in cell development. At the same time, OmicFate provides insights into exogenous cellular interactions in early lineage differentiation, emphasizing the importance of phylogenetics in understanding the differentiation process.

2 Directory structure

.
├── omicfate                  # Main Python package
├── experiment                # Documentation files
├── LICENSE
└── README.md

3 Getting Started

You can use pip install -U omicfate for installation.

4 Contact

• Zehua Zeng (starlitnightly@gmail.com or zehuazeng@xs.ustb.edu.cn)

5 Other

If you would like to sponsor the development of our project, you can go to the afdian website (https://afdian.net/a/starlitnightly) and sponsor us.

Copyright © 2024 112 Lab.
This project is GPL3.0 licensed.