semvec/pypi-packages huggingface dataset:
mkdocs-ubleiden-theme 1.2.0
UBL theme for MkDocs, extending Material for MkDocs
Requires Python: >=3.8
Keywords: mkdocs, theme

# MkDocs UBL theme for documentation

MkDocs UBL is a theme for writing documentation using the Leiden University
Libraries style and colors.
MkDocs UBL template is based on [Material for MkDocs][1]; a theme for 
[MkDocs][2].
MkDocs is static site generator geared towards (technical) project
documentation.

[1]: https://squidfunk.github.io/mkdocs-material/
[2]: https://www.mkdocs.org

## Installation

The MkDocs UBL theme can be installed with `pip`:

First, make sure you have installed [Python v3.*][py] on your machine.
During the installation you will be asked if you also want to install 'pip'.
Do so, and then run the following command to install all the dependencies to
run MkDocs with the theme on your machine:

[py]: https://www.python.org/downloads/

```shell
pip install mkdocs-ubleiden-theme
```

This will automatically install compatible versions of all dependencies:
[MkDocs][2], [Material for MkDocs][1], [Markdown][5], [Pygments][6] and
[Python Markdown Extensions][7].
There's no need to install these packages separately.

[5]: https://python-markdown.github.io/
[6]: https://pygments.org/
[7]: https://facelessuser.github.io/pymdown-extensions/

## Using this theme in your project

Following the [Styling your docs guide][style], set the theme to `ubleiden` in
your `mkdocs.yml` configuration file:

```yml
theme: ubleiden
```

or:

```yml
theme:
  name: ubleiden
```

## Generating the documentation

If you have installed Python 3.* and MkDocs, you can use the command
`mkdocs serve`, or `python -m mkdocs serve` in your terminal to serve the
documentation on your development computer.
For example:

```console
C:\Users\username\Documents\my-cool-application> python -m mkdocs serve
```

When you are ready to generate the final documentation files, run
`mkdocs build` to create a static version locally, or `mkdocs gh-deploy` to
build and push the docs to a special branch in your remote git repository.

For more information about generating and publishing the documentation, see
[Deploying your Docs](https://www.mkdocs.org/user-guide/deploying-your-docs/).
PredDNAContam 0.0.4
A Machine Learning Model to Estimate Within-Species DNA Contamination.
Requires Python: >=3.8

# PredDNAContam

PredDNAContam is a tool to Estimate Within-Species DNA Contamination. 


## Input File Format (CSV)

When using **PredDNAContam**, your input data should be in CSV format with the following columns:

| Column  | Description |
|---------|------------|
| GQ      | Genotype quality |
| DP      | Total read depth |
| AF      | Allele frequency |
| VAF     | Variant allele frequency |

### Example CSV File

The input CSV file should be generated from a VCF (Variant Call Format) file that is produced using HaplotypeCaller from GATK.
The following key features should be extracted from the VCF file for each variant to create the CSV.

```csv
GQ,DP,AF,VAF
20,47,0.5,0.23
60,25,0.5,0.24
23,55,0.5,0.78
```


## Download and Installation

To install PredDNAContam, follow these steps:

1. Download the package
You can download the package from PyPI:

👉 PredDNAContam on PyPI 

🔗 https://pypi.org/project/PredDNAContam/#files

Download the file:
📂 preddnacontam-0.0.4.tar.gz 

2. Extract the package

After downloading, unzip the file:

```
tar -xvzf preddnacontam-0.0.4.tar.gz
cd preddnacontam-0.0.4
```

3. Install the package
Inside the extracted directory, run:

```
pip install .
```

## Running PredDNAContam
1. Modify the configuration file

Navigate to the scripts directory and update config.txt to set the correct paths for your input files, and output directory.

2. Run the tool 
After configuring the paths, execute PredDNAContam:

```
PredDNAContam
```