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came-0.1.9
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مشاهده بیشتر
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مشاهده بیشتر
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مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
cell-type assignment and gene module extraction of scRNA-seq
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | came-0.1.9 |
| نام | came |
| نسخه کتابخانه | 0.1.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Xingyan Liu |
| ایمیل نویسنده | 544568643@qq.com |
| آدرس صفحه اصلی | https://github.com/XingyanLiu/CAME |
| آدرس اینترنتی | https://pypi.org/project/came/ |
| مجوز | MIT |
# CAME
**English** | [简体中文](README_CH.md)
CAME is a tool for **Cell-type Assignment and Module Extraction**, based on a heterogeneous graph neural network.
For detailed usage, please refer to [CAME-Documentation](https://xingyanliu.github.io/CAME/index.html).
<img src="docs/_images/Fig1ABC.png" width="600"/>
CAME outputs the quantitative cell-type assignment for each query cell, that is,
the probabilities of cell types that exist in the reference species, which
enables the identification of the unresolved cell states in the query data.
Besides, CAME gives the aligned cell and gene embeddings across species, which
facilitates low-dimensional visualization and joint gene-module extraction.
<img src="docs/_images/Fig1D.png" width="600"/>
### Installation
It's recommended to create a conda environment for running CAME:
```shell
conda create -n env_came python=3.8
conda activate env_came
```
Install required packages:
```shell
pip install "scanpy[leiden]"
pip install torch # >=1.8
pip install dgl # tested on 0.7.2
```
See [Scanpy](https://scanpy.readthedocs.io/en/stable/),
[PyTorch](https://pytorch.org/) and [DGL](https://www.dgl.ai/)
for detailed installation guide (especially for GPU version).
Install CAME by PyPI:
```shell
pip install came
```
Install the developmental version of CAME from source code:
```shell
git clone https://github.com/XingyanLiu/CAME.git
cd CAME
python setup.py install
```
### Example data
The test code is based on the sample data attached to the CAME package.
It is initially saved in compressed form (`CAME/came/sample_data.zip`),
and will be automatically decompressed to the default directory
(`CAME/came/sample_data/`) when necessary, which contains the following files:
- gene_matches_1v1_human2mouse.csv (optional)
- gene_matches_1v1_mouse2human.csv (optional)
- gene_matches_human2mouse.csv
- gene_matches_mouse2human.csv
- raw-Baron_mouse.h5ad
- raw-Baron_human.h5ad
You can access these data by ``came.load_example_data()``.
If you tend to apply CAME to analyze your own datasets, you need to
prepare at least the last two files for the same species (e.g., cross-dataset
integration);
For cross-species analysis, you need to provide another `.csv`
file where the first column contains the genes in the reference species and the
second contains the corresponding query homologous genes.
> NOTE:
> the file `raw-Baron_human.h5ad` is a subsample from the original data
> for code testing. The resulting annotation accuracy may not be as good as
> using the full dataset as the reference.
### Test CAME's pipeline (optional)
To test the package, run the python file `test_pipeline.py`:
```python
# test_pipeline.py
import came
if __name__ == '__main__':
came.__test1__(6, batch_size=2048)
came.__test2__(6, batch_size=None)
```
```shell
python test_pipeline.py
```
### Contribute
* Issue Tracker: https://github.com/XingyanLiu/CAME/issues
* Source Code:
* https://github.com/zhanglabtools/CAME
* https://github.com/XingyanLiu/CAME (the developmental version)
### Support
If you are having issues, please let us know. We have a mailing list located at:
* xingyan@amss.ac.cn
* 544568643@qq.com
### Citation
If CAME is useful for your research, consider citing our preprint:
> Cross-species cell-type assignment of single-cell RNA-seq by a heterogeneous graph neural network.
Xingyan Liu, Qunlun Shen, Shihua Zhang.
bioRxiv 2021.09.25.461790; doi: https://doi.org/10.1101/2021.09.25.461790
نیازمندی
| مقدار | نام |
|---|---|
| - | scanpy |
| - | torch |
| - | dgl |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8.0 | Python |
نحوه نصب
نصب پکیج whl came-0.1.9:
pip install came-0.1.9.whl
نصب پکیج tar.gz came-0.1.9:
pip install came-0.1.9.tar.gz