Unravelling three-dimensionally dynamics of spatial multi-modal data with RidgeSpace

You can freely use RidgeSpace for illustrating, comparing, and tracking the spatial dynamics of molecular signals.

Overview of RidgeSpace.

Prerequisites

"matplotlib", "numpy", "pandas", "scipy"

Installation

I suggest that you can freely install RidgeSpace with pip.

pip install RidgeSpace

You can also use a separate conda environment for installing RidgeSpace.

conda create -y -n RidgeSpace_env python=3.7
source activate RidgeSpace_env
pip install RidgeSpace

Basic Examples

Examples of RidgeSpace.

Test data and code for RidgeSpace provided in the "tests" folder.

Single-gene spatial depiction:

RidgeSpace.pl_single(adata, plot_name = 'Mbp', obs_cluster='Clusters', elev=40, view=160))

Multi-modal spatial comparison:

RidgeSpace.pl_multipleOUT(adata, plot_nameA = 'Tnnt1', plot_nameB = 'Tnnt2', obs_cluster='Clusters', elev=20, view=160, plot_HE_bg=True)

Pseudotime spatial trajectory representation:

RidgeSpace.pl_trajectory(adata, plot_name = 'Pseudotime', obs_cluster='Clusters', elev=45, view=165, HE_z=10)

Further tutorials please refer to https://RidgeSpace.readthedocs.io/.