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cytomulate-0.1.0
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مشاهده بیشترتوضیحات
Accurate and Efficient Simulation of CyTOF data
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | cytomulate-0.1.0 |
| نام | cytomulate |
| نسخه کتابخانه | 0.1.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Yuqiu Yang, Kevin Wang, Tao Wang, Sherry Wang |
| ایمیل نویسنده | yuqiuy@smu.edu, kevinwang@smu.edu, Tao.Wang@UTSouthwestern.edu, swang@smu.edu |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/cytomulate/ |
| مجوز | - |
# cytomulate
> A simulation package for Cytometry by Time-of-Flight (CyTOF)
[](https://forthebadge.com)
[](https://forthebadge.com)
| Branch | Release | CI/CD | Documentation | Code Coverage |
| --- | --- | --- | --- | --- |
| main |  |  | [](https://cytomulate.readthedocs.io/en/main/?badge=main) | [](https://codecov.io/gh/kevin931/cytomulate) |
| dev |  | | [](https://cytomulate.readthedocs.io/en/dev/?badge=dev) | [](https://codecov.io/gh/kevin931/cytomulate) |
## Installation
You can easily install ``cytomulate`` from either ``PyPI`` or ``conda``. For the former, use the following command:
```shell
pip install cytomulate
```
Or if you are using a conda environment, you can use the following command:
```shell
conda install -c normalizingflow cytomulate
```
If you wish to use ``PyCytoData``, you can install separately with more instructions [here](https://cytomulate.readthedocs.io/en/dev/installation.html).
## Examples
We have two modes: **Creation Mode** and **Emulation Mode**. The former is probabilistic-model based simulation without the need of datasets; the latter is based on existing datasets to match as much of the existing features as possible. Here, we give two quick examples of how they work.
### Creation Mode
To create your datasets, you can run the following:
```python
>>> from cytomulate import CreationCytofData
>>> cytof_data = CreationCytofData()
>>> cytof_data.initialize_cell_types()
>>> expression_matrices, labels, _, _ = cytof_data.sample(n_samples = 1000)
```
The ``expression_matrices`` is a dictionary that contains the expression matrix from each sample. Correspondingly, ``labels`` is a dictionary that contains their cell types.
### Emulation Mode
This is a little bit more involved because we need existing data! If you already have your data, congratulations, you are good to go! For this demonstration, we use ``PyCytoData`` to load some example datasets instead (Of course, you will need to install [PyCytoData](https://pycytodata.readthedocs.io/en/latest/index.html) first if you wish to use it):
```python
>>> from cytomulate import EmulationCytoData
>>> from PyCytoData import DataLoader
>>> exprs = DataLoader.load_dataset(dataset="levine13")
>>> exprs.preprocess(arcsinh=True)
>>> cytof_data = EmulationCytofData()
>>> cytof_data.initialize_cell_types(expression_matrix=exprs.expression_matrix,
... labels=exprs.cell_types)
>>> expression_matrices, labels, _, _ = cytof_data.sample(n_samples = 1000)
```
This is it!
### Working with PyCytoData
We're fully compatible with ``PyCytoData``! As you've seen above, you can use ``PyCytoData`` to download datasets! If you're familiar with that interface and in love with its easy workflow, you can have ``cytomulate`` output a ``PyCytoData`` object as well:
```python
>>> from cytomulate import CreationCytofData
>>> cytof_data = CreationCytofData()
>>> cytof_data.initialize_cell_types()
>>> simulation_data = cytof_data.sample_to_pycytodata(n_samples = 1000)
```
This will allow you to use all the downstream capabilities of ``PyCytoData``.
### Command-Line Interface (CLI)
If you prefer to use cytomulate from the command-line, you've got that option as well! One **caveat** is that this mode requires ``PyCytoData`` to be installed. To run the Creation Mode, you can do:
```shell
python -m cytomulate \
--creation \
--n_cells 1000 \
-o <your_dir_here>
```
To run the emulation mode, you can run the following:
```shell
python -m cytomulate \
--emulation \
--n_cells 1000 \
-o <your_dir_here> \
--exprs <you_path_to_exprssion_matrix> \
--cell_types <you_path_to_cell_types>
```
Of course, we have much more customization options! For more details, read our [tutorial here](https://cytomulate.readthedocs.io/en/dev/tutorial/cli.html).
## Documentation
For more detailed documentation on ``cytomulate``, please visit our [website](https://cytomulate.readthedocs.io/)! You will find detailed tutorials,
guidelines, development guides, etc.
Our documentation is built automatically on the cloud! If you wish to build locally, check our detailed guide [here](https://cytomulate.readthedocs.io/en/latest/change/build.html)!
## Latest Release: v0.1.0
Our **FIRST OFFICIAL RELEASE** is here! From now on, all our releases will be supported with our standard support cycle. Here you will find our release notes.
### Changes and New Features
- Added Command-Line Interface with support for complex simulations
- Improved docstrings
- Improved documentations with tutorials
### From Pre-release
These are listed for documetation reasons for the first official release.
- Support for ``Emulation Mode`` and ``Creation Mode``
- Support for complex simulations
- Availability on ``PyPI`` and ``conda``
## References
If you are cytomulating in your workflow, citing [our paper](https://doi.org/10.1101/2022.06.14.496200) is appreciated:
```
@article {Yang2022.06.14.496200,
author = {Yang, Yuqiu and Wang, Kaiwen and Lu, Zeyu and Wang, Tao and Wang, Xinlei},
title = {Cytomulate: Accurate and Efficient Simulation of CyTOF data},
elocation-id = {2022.06.14.496200},
year = {2022},
doi = {10.1101/2022.06.14.496200},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2022/06/16/2022.06.14.496200},
eprint = {https://www.biorxiv.org/content/early/2022/06/16/2022.06.14.496200.full.pdf},
journal = {bioRxiv}
}
```
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| - | scipy |
| - | scikit-learn |
| - | networkx |
| - | matplotlib |
| - | tqdm |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.5 | Python |
نحوه نصب
نصب پکیج whl cytomulate-0.1.0:
pip install cytomulate-0.1.0.whl
نصب پکیج tar.gz cytomulate-0.1.0:
pip install cytomulate-0.1.0.tar.gz