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Project description
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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)
# 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
# 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
docker pull 2003100127/tresor
4. Github
# 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.
@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 pages.
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