Metadata-Version: 2.1
Name: scAnnot
Version: 0.0.1
Summary: single cell annotation
Home-page: https://github.com/changebio/scAnnot
Author: Yin Huang
Author-email: changebio@yeah.net
License: Apache Software License 2.0
Keywords: nbdev jupyter notebook python
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE

scAnnot
================

<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->

This file will become your README and also the index of your
documentation.

## Install

``` sh
pip install scAnnot
```

## How to use

### In command line

#### 1. output the table of predicted lables in csv format

    scAnnot /home/huang_ziliang/project/brain/data/public/human_brain_glial_Fu_2021_PCR/h5/umap.h5ad --output test.csv

#### 2. output the anndata with predicted lables in h5ad

    scAnnot /home/huang_ziliang/project/brain/data/public/human_brain_glial_Fu_2021_PCR/h5/umap.h5ad --output test.h5ad

### In jupyter notebook

    ad=scAnnot('/home/huang_ziliang/project/brain/data/public/human_brain_glial_Fu_2021_PCR/h5/umap.h5ad')

    #show umap from the latent space
    ad=scAnnot('/home/huang_ziliang/project/brain/data/public/human_brain_glial_Fu_2021_PCR/h5/umap.h5ad',show=True)


