TrajAtlas 0.3.1

TrajAtlas, a trajectory-centric framework reveals differentiation heterogenity among cells, genes, and gene modules

Unraveling multi-scale differentiation heterogeneity with trajectory-centric framework

The central idea of TrajAtlas revolves around axis-based analysis. Although initially designed for osteogenesis datasets, it can be applied to almost any type of dataset as long as you have an "axis" (such as pseudotime or gene expression patterns).

Getting started

Please refer to the documentation. In particular:

• API documentation
• Introduction
• Tutorial

If you want to do pseudotime analysis, please check

Differential Abundance analysis

Differential Expression analysis

If you are interested in gene expression programs, we have developed a pipeline based on it. Please check

TrajAtlas meets gene expression program

If you are using gene set scoring for function inference, you can utilize TrajAtlas to identify which genes are more significant within the gene sets.

TrajAtlas meets gene set scoring TrajAtlas meets spatial omic

If you have osteogenesis datasets, you can project your datasets onto our model.

Projecting osteogenesis datasets

Installation

You need to have Python 3.8 or newer installed on your system. If you don't have Python installed, we recommend installing Mamba.

You can install TrajAtlas with following codes

pip install TrajAtlas

Citation

TrajAtlas recently has posted on bioRxiv. If TrajAtlas helps you, please cite our work.