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kevlar-dev / kevlar

Reference-free variant discovery in large eukaryotic genomes
https://kevlar.readthedocs.io
MIT License
40 stars 9 forks source link
dna genome-variation genomics variant-calling

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kevlar build status PyPI version Test coverage kevlar documentation Docker build status MIT licensed

What if I told you we don't need alignments to find variants?

kevlar

Daniel Standage, 2016-2019
https://kevlar.readthedocs.io

Welcome to kevlar, software for predicting de novo genetic variants without mapping reads to a reference genome! kevlar's k-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model. This software is free for use under the MIT license.

Where can I find kevlar online?
  • Source repository: https://github.com/kevlar-dev/kevlar
  • Documentation: https://kevlar.readthedocs.io
  • Stable releases: https://github.com/kevlar-dev/kevlar/releases
  • Issue tracker: https://github.com/kevlar-dev/kevlar/issues
If you have questions or need help with kevlar, the [GitHub issue tracker](https://github.com/kevlar-dev/kevlar) should be your first point of contact.
How do I install kevlar? See [the kevlar documentation](http://kevlar.readthedocs.io/en/latest/install.html) for complete instructions, but the impatient can try the following. ``` pip3 install git+https://github.com/dib-lab/khmer.git pip3 install biokevlar ```
How do I use kevlar?
  • Installation instructions: http://kevlar.readthedocs.io/en/latest/install.html
  • Quick start guide: http://kevlar.readthedocs.io/en/latest/quick-start.html
  • Tutorial: http://kevlar.readthedocs.io/en/latest/tutorial.html
How do I cite kevlar? Standage DS, Brown CT, Hormozdiari F (2019) Kevlar: a mapping-free framework for accurate discovery of de novo variants. *bioRxiv*, [doi:10.1101/549154](https://doi.org/10.1101/549154).
How can I contribute? We welcome contributions to the kevlar project from the community! If you're interested in modifying kevlar or contributing to its ongoing development, feel free to send us a message or submit a pull request! The kevlar software is a project of the [Lab for Data Intensive Biology](http://ivory.idyll.org/lab/) and the [Computational Genomics Lab](http://www.hormozdiarilab.org/) at UC Davis.