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# Welcome to MkDocs | ||
# scdataloader | ||
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For full documentation visit [mkdocs.org](https://www.mkdocs.org). | ||
[![codecov](https://codecov.io/gh/jkobject/scDataLoader/branch/main/graph/badge.svg?token=scDataLoader_token_here)](https://codecov.io/gh/jkobject/scDataLoader) | ||
[![CI](https://github.com/jkobject/scDataLoader/actions/workflows/main.yml/badge.svg)](https://github.com/jkobject/scDataLoader/actions/workflows/main.yml) | ||
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## Commands | ||
Awesome single cell dataloader created by @jkobject | ||
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* `mkdocs new [dir-name]` - Create a new project. | ||
* `mkdocs serve` - Start the live-reloading docs server. | ||
* `mkdocs build` - Build the documentation site. | ||
* `mkdocs -h` - Print help message and exit. | ||
This data loader is designed to be used with: | ||
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## Project layout | ||
- [lamindb](https://lamin.ai/) | ||
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mkdocs.yml # The configuration file. | ||
docs/ | ||
index.md # The documentation homepage. | ||
... # Other markdown pages, images and other files. | ||
and: | ||
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- [scanpy](https://scanpy.readthedocs.io/en/stable/) | ||
- [anndata](https://anndata.readthedocs.io/en/latest/) | ||
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It allows you to: | ||
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1. load thousands of datasets containing millions of cells in a few seconds. | ||
2. preprocess the data per dataset and download it locally (normalization, filtering, etc.) | ||
3. create a more complex single cell dataset | ||
4. extend it to your need | ||
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## Install it from PyPI | ||
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```bash | ||
pip install scdataloader | ||
``` | ||
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## Usage | ||
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see the notebooks in [docs](https://jkobject.github.io/scDataLoader/): | ||
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1. [load a dataset](https://jkobject.github.io/scDataLoader/notebooks/01_load_dataset.html) | ||
2. [create a dataset](https://jkobject.github.io/scDataLoader/notebooks/02_create_dataset.html) | ||
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## Development | ||
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Read the [CONTRIBUTING.md](CONTRIBUTING.md) file. |
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