# MetaChat
## Brief introduction
MetaChat is a Python package to screen metabolic cell communication (MCC) from spatial multi-omics data of transcriptomics and metabolomics.
It contains many intuitive visualization and downstream analysis tools, provides a great practical toolbox for biomedical researchers.
### Metabolic cell communication
Metabolic cell-cell communication (MCC) occurs when sensor proteins in the receiver cells detect metabolites in their environment, activating intracellular signaling events. There are three major potential sensors of metabolites: surface receptors, nuclear receptors, and transporters. Metabolites secreted from cells are either transported over short-range distances (a few cells) via diffusion through extracellular space, or over long-range distances via the bloodstream and the cerebrospinal fluid (CSF).
<img width="600" alt="image" src="https://github.com/SonghaoLuo/MetaChat/assets/138028157/f08f21de-eeae-4626-8fbe-c26a307ec225">
### MetaChatDB
MetaChatDB is a literature-supported database for metabolite-sensor interactions for both human and mouse. All the metabolite-sensor interactions are reported based on peer-reviewed publications. Specifically, we manually build MetaChatDB by integrating three high-quality databases (PDB, HMDB, UniProt) that are being continually updated.
<img width="700" alt="image2" src="https://github.com/user-attachments/assets/1601f7f1-0997-4bdf-96da-5d2ae1fd28a2" />
### Documentation, and Tutorials
For more basic tutorial and real data examples, please see MetaChat documentation that is available through the link https://metachat.readthedocs.io/en/latest/.
### Analysis pipeline
<img width="2000" height="7914" alt="Table2" src="https://github.com/user-attachments/assets/d018be0e-fad2-4c74-b91e-4c0d929851c1" />
## Installation
### System requirements
Recommended operating systems: macOS or Linux. MetaChat was developed and tested on Linux and macOS.
### Python requirements
MetaChat was developed using python 3.9.
### Installation using `pip`
We suggest setting up MetaChat in a separate `mamba` or `conda` environment to prevent conflicts with other software dependencies. Create a new Python environment specifically for MetaChat and install the required libraries within it.
```bash
mamba create -n metachat_env python=3.9 r-base=4.3.2
mamba activate metachat_env
pip install metachat
```
if you use `conda`, `r-base=4.3.2` may not included in the channels. Instead, you can `r-base=4.3.1` in `conda`.
## Reference
Luo S., Almet A.A., Zhao W., He C., Tsai Y.-C., Ozaki H., Sugita B.K., Du K., Shen X., Cao Y., Yang Q., Watanabe M., Nie Q.* Spatial metabolic communication flow of cells.
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"description": "# MetaChat\n## Brief introduction\nMetaChat is a Python package to screen metabolic cell communication (MCC) from spatial multi-omics data of transcriptomics and metabolomics. \nIt contains many intuitive visualization and downstream analysis tools, provides a great practical toolbox for biomedical researchers.\n\n### Metabolic cell communication\nMetabolic cell-cell communication (MCC) occurs when sensor proteins in the receiver cells detect metabolites in their environment, activating intracellular signaling events. There are three major potential sensors of metabolites: surface receptors, nuclear receptors, and transporters. Metabolites secreted from cells are either transported over short-range distances (a few cells) via diffusion through extracellular space, or over long-range distances via the bloodstream and the cerebrospinal fluid (CSF).\n\n<img width=\"600\" alt=\"image\" src=\"https://github.com/SonghaoLuo/MetaChat/assets/138028157/f08f21de-eeae-4626-8fbe-c26a307ec225\">\n\n### MetaChatDB\nMetaChatDB is a literature-supported database for metabolite-sensor interactions for both human and mouse. All the metabolite-sensor interactions are reported based on peer-reviewed publications. Specifically, we manually build MetaChatDB by integrating three high-quality databases (PDB, HMDB, UniProt) that are being continually updated.\n\n<img width=\"700\" alt=\"image2\" src=\"https://github.com/user-attachments/assets/1601f7f1-0997-4bdf-96da-5d2ae1fd28a2\" />\n\n### Documentation, and Tutorials\nFor more basic tutorial and real data examples, please see MetaChat documentation that is available through the link https://metachat.readthedocs.io/en/latest/.\n\n### Analysis pipeline\n\n<img width=\"2000\" height=\"7914\" alt=\"Table2\" src=\"https://github.com/user-attachments/assets/d018be0e-fad2-4c74-b91e-4c0d929851c1\" />\n\n## Installation\n### System requirements\nRecommended operating systems: macOS or Linux. MetaChat was developed and tested on Linux and macOS.\n### Python requirements\nMetaChat was developed using python 3.9.\n### Installation using `pip`\nWe suggest setting up MetaChat in a separate `mamba` or `conda` environment to prevent conflicts with other software dependencies. Create a new Python environment specifically for MetaChat and install the required libraries within it.\n\n```bash\nmamba create -n metachat_env python=3.9 r-base=4.3.2\nmamba activate metachat_env\npip install metachat\n```\nif you use `conda`, `r-base=4.3.2` may not included in the channels. Instead, you can `r-base=4.3.1` in `conda`.\n\n\n\n## Reference\nLuo S., Almet A.A., Zhao W., He C., Tsai Y.-C., Ozaki H., Sugita B.K., Du K., Shen X., Cao Y., Yang Q., Watanabe M., Nie Q.* Spatial metabolic communication flow of cells.\n",
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