Reference-free variant discovery in large eukaryotic genomes
Clone or download
standage Updates to documentation (#300)
This update cleans up the documentation in preparation for the version 0.6 release. Updates include:

- refined installation instructions, especially replacing `pip` with `pip3`
- a new brief glossary of relevant terms
- minor updates to the quick start docs
- a small bug fix in `kevlar partition` relevant to the quick start results

Closes #280. Closes #296.
Latest commit 0a13ca0 Nov 14, 2018

README.md

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
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) as well as short, medium and long insertion/deletion variants (indels) simultaneously. This software is free for use under the MIT license.

Where can I find kevlar online?

If you have questions or need help with kevlar, the GitHub issue tracker should be your first point of contact.

How do I install kevlar?

See the kevlar documentation 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?
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 and the Computational Genomics Lab at UC Davis.