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Damage parameter estimation for ancient DNA

Project description

PyDamage

PyDamage

Pydamage, is a Python software to automate the process of contig damage identification and estimation. After modelling the ancient DNA damage using the C to T transitions, Pydamage uses a likelihood ratio test to discriminate between truly ancient, and modern contigs originating from sample contamination.

Installation

With conda (recommended)

conda install -c bioconda pydamage

With pip

pip install pydamage

Install from source to use the development version

Using pip

pip install git+ssh://git@github.com/maxibor/pydamage.git@dev

By cloning in a dedicated conda environment

git clone git@github.com:maxibor/pydamage.git
cd pydamage
git checkout dev
conda env create -f environment.yml
conda activate pydamage
pip install -e .

Running tests

python -m pytest

Quick start

pydamage --outdir result_directory analyze aligned.bam

Note that if you specify --outdir, it has to be before the PyDamage subcommand, example: pydamage --outdir test filter pydamage_results.csv

CLI help

Command line interface help message

pydamage --help

Documentation

pydamage.readthedocs.io

Cite

PyDamage has been published in PeerJ: 10.7717/peerj.11845

@article{borry_pydamage_2021,
    author = {Borry, Maxime and Hübner, Alexander and Rohrlach, Adam B. and Warinner, Christina},
    doi = {10.7717/peerj.11845},
    issn = {2167-8359},
    journal = {PeerJ},
    language = {en},
    month = {July},
    note = {Publisher: PeerJ Inc.},
    pages = {e11845},
    shorttitle = {PyDamage},
    title = {PyDamage: automated ancient damage identification and estimation for contigs in ancient DNA de novo assembly},
    url = {https://peerj.com/articles/11845},
    urldate = {2021-07-27},
    volume = {9},
    year = {2021}
}

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