semvec/pypi-packages huggingface dataset:
zfl-ai 0.0.15
ai on zfl
Requires Python: >=3.6

# zfl-ai

[![PyPI - Version](https://img.shields.io/pypi/v/django-hatch.svg)](https://pypi.org/project/django-hatch)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/django-hatch.svg)](https://pypi.org/project/django-hatch)

![zfl-ai_1](https://github.com/kenno-warise/zfl-ai/assets/51676019/8ed643a6-140f-447d-89cd-932da3f462b9)

-----

**目次**

- [詳細](#詳細)
- [インストールとDjangoプロジェクト作成](#インストールとDjangoプロジェクト作成)
- [Djangoプロジェクトにプラグイン](#Djangoプロジェクトにプラグイン)
- [License](#license)

## 詳細

djangoプロジェクトでインストールできるDjangoアプリです。

使用方法は以下からご覧ください。

## インストールとDjangoプロジェクト作成

実行環境は「Python3.7」、「Django2.2.5」です。

```console
$ python3 --version
Python 3.7.0
```

Djangoアプリはpipでインストールします。

```console
$ pip install zfl-ai
```

Djangoプロジェクトを作成

```console
$ django-admin startproject myproject .
```

言語を設定します。

`myproject/settings.py`

```python
# Internationalization
# https://docs.djangoproject.com/en/4.2/topics/i18n/

LANGUAGE_CODE = 'ja'

TIME_ZONE = 'Asia/Tokyo'

USE_I18N = True

USE_TZ = True
```

## Djangoプロジェクトにプラグイン

Djangoアプリを設定します。

`myproject/settings.py`

```python
INSTALLED_APPS = [
    ...,
    "ai",
]
```

プロジェクト直下のtemplatesを読み込むように設定。

```python
TEMPLATES = [
    {
        ...
        'DIRS': [os.path.join(BASE_DIR, 'templates')],
        ...
    },
]
```

`myproject/urls.py`

```python
...
from django.urls import path, include

urlpatterns = [
    ...,
    path('', include('ai.urls')),
]
```

zfl-aiのテンプレートである「index.html」ではテンプレートタグ「{% extends '...' %}」で「base.html」を読み込むように設定しているので、「templates/base.html」を作成する必要があります。

```console
$ mkdir templates && touch templates/base.html
```

base.htmlの内容

```html
{% load static %}
<html lang="ja" prefix="og: http://ogp.me/ns#">
  <head>

    <!-- BootStrap CSS Link -->
    <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.3.1/css/bootstrap.min.css" integrity="sha384-ggOyR0iXCbMQv3Xipma34MD+dH/1fQ784/j6cY/iJTQUOhcWr7x9JvoRxT2MZw1T" crossorigin="anonymous">


    <!-- StaticFiles CSS -->
    {% block ai-style %}{% endblock %}

  </head>
  <body>

    <!-- Djangoテンプレートタグ -->

    {% block content %}
    {% endblock %}

    <!-- BootStrap jQuery -->
    <script src="https://code.jquery.com/jquery-3.3.1.slim.min.js" integrity="sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo" crossorigin="anonymous"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.14.7/umd/popper.min.js" integrity="sha384-UO2eT0CpHqdSJQ6hJty5KVphtPhzWj9WO1clHTMGa3JDZwrnQq4sF86dIHNDz0W1" crossorigin="anonymous"></script>
    <script src="https://stackpath.bootstrapcdn.com/bootstrap/4.3.1/js/bootstrap.min.js" integrity="sha384-JjSmVgyd0p3pXB1rRibZUAYoIIy6OrQ6VrjIEaFf/nJGzIxFDsf4x0xIM+B07jRM" crossorigin="anonymous"></script>

  </body>
</html>
```


サーバーを起動します。

```console
$ python3 manage.py runserver
```

`127.0.0.1:8000/ai/`にアクセスします。

## License

`zfl-ai` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
Geva 1.0.2
A genomic assement tools including Completeness and Accuracy
Requires Python: >=3.7

# GEVA Criteria for Completeness and Accuracy of Assemblies Assessment
## Assessment
GEVA is a software package for the completeness and accuracy assessment for genome assemblies.  

GEVA concludes 5 criteria for the assessment of synthetic datasets, three criteria are used to measure completeness, namely completeness rate (CR), single-copy completeness rate (SCR), and duplicated completeness rate (DCR). To evaluate the assembly accuracy, we announces two criteria, the average proportion of the largest category (APLC), and the average distance difference (ADF).   

GEVA is a software package written in python. ASSca5 runs as a command-line program with a variety of user-options and is freely available for download below, compatible for Unix/Linux/Mac OS.  


## Prerequisite
> * Python 3.7 (tested with Python v3.7.12) or higher
> * pandas v1.1.4 or higher

## Installation
You can compile a static version using the following command:  
```
  #Github
  git clone https://github.com/panlab-bioinfo/Geva.git
  cd Geva & chmod +x geva.py

  #pypi
  pip install geva==latest    
```  

## Usage
`geva.py` is a python script used a reference genome and a assembly to assess synthetic datasets, which contains 5 parameters:  

    geva.py [-h] -i INPUT -r REFERENCE [-k KMER_LENGTH] [-s SAMPLE] -o OUT_PREFIX  

where `-i` sets a input file of fasta format in use; `-r` sets the reference genome of assembly with fasta format; `-k` specifies the k-mer length used to assess the assembly, and the default value is `21`; `-s` means the number of reference unique k-mer used in the the assessment, the default value is `"all"`, using all reference unique kmers to assess the assembly will be slow for some complex genomes, so randomly sampling some reference unique kmers for assessment will greatly speed up the script and memory consumption, and we recommend the k is `200,000`; `-o` specifies the prefix of output files. 

For example, a typical assessment command line looks like:  

    geva.py -i haplotype.fasta -r haplotype_ref.fasta -o test  

If the process of this script is running out of memory or too slow, we recommend you to use `-s` parameter:

    geva.py -i haplotype.fasta -r haplotype_ref.fasta -s 200000 -o test 


## Citation
If you geva in any published work, please cite the following manuscript:  
***[Yu W, Luo H, Yang J, Zhang S, Jiang H, Zhao X, et al. Comprehensive assessment of 11 de novo HiFi assemblers on complex eukaryotic genomes and metagenomes. Genome Research. 2024](https://pubmed.ncbi.nlm.nih.gov/38428994/);***