Metadata-Version: 2.3
Name: tresor
Version: 0.1.2
Summary: 
Author: Jianfeng Sun
Author-email: jianfeng.sunmt@gmail.com
Requires-Python: >=3.11,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Dist: biopython (>=1.84,<2.0)
Requires-Dist: click (>=8.1.7,<9.0.0)
Requires-Dist: numpy (>=2.0.0,<3.0.0)
Requires-Dist: pandas (>=2.2.2,<3.0.0)
Requires-Dist: pyfastx (>=2.1.0,<3.0.0)
Requires-Dist: pyfiglet (>=1.0.2,<2.0.0)
Requires-Dist: pyyaml (>=6.0.1,<7.0.0)
Requires-Dist: scipy (>=1.14.0,<2.0.0)
Description-Content-Type: text/markdown

<h1 align="center">
    <img src="https://github.com/2003100127/tresor/blob/main/img/Tresor-logo.png?raw=true" width="276" height="114">
    <br>
</h1>

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<hr>

#### Platform

![Python](https://img.shields.io/badge/-Python-000?&logo=Python)
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###### tags: `computational biology`, `sequencing read simulation`

## Overview

Tresor is a Python toolkit for simulating sequencing reads at the single-locus, bulk RNA-seq, and single-cell levels. It is implemented based on phylogenetic tree-based methods, which allows for ultra-fast simulation read generation. Tresor allows both short-read and long-read sequencing read simulation, and substitution and indel (insertion and deletion) errors added to reads. Tresor implements a very flexible read generation framework, which allows users to design their simulated reads in any forms and structures. Tresor can vastly help both computational and experimental researchers to swiftly test their sequencing method ideas.

## Documentation

Please check how to use the full functionalities of Tresor in the documentation https://2003100127.github.io/tresor.

## Installation

### 1. PyPI (recommended)

[tresor homepage](https://pypi.org/project/tresor/)

```shell
# create a conda environment
conda create --name tresor python=3.11

# activate the conda environment
conda activate tresor

# the latest version
pip install tresor --upgrade
```

### 2. Conda

[tresor homepage on Anaconda](https://anaconda.org/Jianfeng_Sun/tresor)

```shell
# create a conda environment
conda create --name tresor python=3.11

# activate the conda environment
conda activate tresor

# the latest version
conda install jianfeng_sun::tresor
```

### 3. Docker

[tresor homepage on Docker](https://hub.docker.com/r/2003100127/tresor)

```shell
docker pull 2003100127/tresor
```

### 4. Github

[tresor homepage on Github](https://github.com/2003100127/tresor)

```shell
# create a conda environment
conda create --name tresor python=3.11

# activate the conda environment
conda activate tresor

# create a folder
mkdir project

# go to the folder
cd project

# fetch Tresor repository with the latest version
git clone https://github.com/2003100127/tresor.git

# enter this repository
cd tresor

# do the following command
pip install .
# or
python setup.py install
```


## Citation

Please cite our work if you use Tresor in your research.
```angular2html
@article{tresor,
    title = {Tresor: Transcriptomic Read Simulation with Realistic PCR Error Representation},
    author = {Jianfeng Sun},
    url = {https://github.com/2003100127/tresor},
    year = {2025},
}
```

## Contact

Please report any questions on [issue](https://github.com/2003100127/tresor/issues) pages.

