Simulator for ddRADseq (double digest restriction site associated DNA sequencing) datasets. Generates reads (FASTQ format) that can be analyzed and validated using a ground truth file (YAML).
Project description
ddRAGE - ddRAD Data Generator
ddRAGE (ddRAD Data Generator) is a software to simulate double digest restriction site associated DNA sequencing reads. The generated data sets can be used to test ddRAD analysis tools and validate their results.
The documentation, including a tutorial, can be found here. The code is hosted on bitbucket, PyPI, and bioconda.
System Requirements
python >= 3.8
numba
numpy
matplotlib
pyyaml
scipy
seaborn
For the docs:
sphinx
For parameter visualization:
bokeh >= 3.1.1
Installation
We recommend the installation using conda:
$ conda create -n ddrage -c bioconda ddrage
$ source activate ddrage
Alternatively, you can download the source code from bitbucket and install it using pip:
$ git clone https://bitbucket.org/genomeinformatics/rage.git ddrage
$ cd ddrage
/ddrage$ pip install . # basic version
# OR
# to install with support to build the documentation and visualize bbd parameters
/ddrage$ pip install .[documentation,BBD-visualization]
Usage
To simulate a ddRAD data set, call ddrage from the command line:
$ ddrage
you can specify parameters to change data set parameters such as number of individuals (-n), nr of loci (-l), and coverage (--coverage):
$ ddrage -n 6 -l 10000 --coverage 30
This creates a data set with reads from 6 individuals at 10000 loci with an expected coverage of 30.
A more detailed tutorial can be found on readthedocs.
Citing ddRAGE
Our paper describing ddRAGE has been published in Molecular Ecology Resources. You can cite it as follows:
Timm H, Weigand H, Weiss M, Leese F, Rahmann S. ddRAGE: A data set generator to evaluate ddRADseq analysis software. Mol Ecol Resour. 2018;18:681–690. https://doi.org/10.1111/1755-0998.12743
BibTeX version:
@article{timm2018ddrage,
title={ddrage: A data set generator to evaluate ddRADseq analysis software},
author={Timm, Henning and Weigand, Hannah and Weiss, Martina and Leese, Florian and Rahmann, Sven},
journal={Molecular Ecology Resources},
volume={18},
number={3},
pages={681--690},
year={2018},
url = {http://dx.doi.org/10.1111/1755-0998.12743},
doi = {10.1111/1755-0998.12743},
}
The source code itself is also published on Zenodo under the DOI 10.5281/zenodo.4390216.
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