MorphLink: Bridging Cell Morphological Behaviors and Molecular Dynamics in Multi-modal Spatial Omics
Jing Huang, Chenyang Yuan, Jiahui Jiang, Jianfeng Chen, Sunil S. Badve, Yesim Gokmen-Polar, Rossana L. Segura, Xinmiao Yan, Alexander Lazar, Jianjun Gao, Michael Epstein, Linghua Wang* and Jian Hu*
MorphLink is a computational framework to systematically extract and link interpretable morphological features with molecular measurements in multi-model spatial omics analyses. The identified linkages provide a transparent depiction of cellular behaviors that drive transcriptomic heterogeneity and immune diversity across different regions within diseased tissues. Moreover, MorphLink is scalable and robust against cross-sample batch effects, making it an efficient method for integrating spatial omics data analysis across samples, cohorts, and modalities, and enhancing the interpretation of results for large-scale studies. MorphLink is applicable to various types of spatial omics data, including spatial transcriptomics (Spatial Transcriptomics, 10x Visium, 10x Xenium, and MERFISH), spatial proteomics (CODEX and IMS), and the simultaneous measurement of proteins and transcriptome (spatial CITE-seq and CosMx).
For thorough details, see the preprint: Biorxiv
With MorphLink package, you can:
- Extract interpretable morphological features from histology images in a label-free manner.
- Quantify the relationships between cell morphological and molecular features in a spatial context.
- Visually examine how cellular behavior changes from both morphological and molecular perspectives.
For the step-by-step tutorial, please refer to:
https://github.com/jianhuupenn/MorphLink/blob/main/tutorial/tutorial.md
A Jupyter Notebook of the tutorial is accessible from :
https://github.com/jianhuupenn/MorphLink/blob/main/tutorial/tutorial.ipynb
Please install Jupyter in order to open this notebook.
Toy data and results can be downloaded at:
https://drive.google.com/drive/folders/1NgJICg1jFD2HP7WGZ9vXk7GrRJRoFfSD?usp=sharing
https://github.com/jianhuupenn/MorphLink/blob/main/tutorial/results
https://github.com/jianhuupenn/MorphLink/blob/main/tutorial/figures
Python support packages: pandas, numpy, numba, scipy, scanpy, anndata, scikit-learn, scikit-image, matplotlib, imutils, opencv-python.
Environment 1:
- System: Mac OS Sonoma 14.0
- Python: 3.11.5
- Python packages: pandas = 2.1.4, numpy = 1.26.2, numba = 0.58.1, scipy = 1.11.4, scanpy = 1.9.6, anndata = 0.10.3, scikit-learn = 1.3.2, scikit-image = 0.23.2, matplotlib = 3.8.2, imutils = 0.5.4, opencv-python = 4.8.1.
Environment 2:
- System: Anaconda (23.9.0)
- Python: 3.11.5
- Python packages: pandas = 2.0.3, numpy = 1.24.3, numba = 0.57.1, scipy = 1.11.1, scanpy = 1.9.8, anndata = 0.10.8, scikit-learn = 1.3.0, scikit-image = 0.20.0, matplotlib = 3.7.2, imutils = 0.5.4, opencv-python = 4.10.0.
Souce code: Github
We are continuing adding new features. Bug reports or feature requests are welcome.
Last update: 06/23/2024, version 1.0.1
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