DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
- DeepVariant release notes
- Building and testing DeepVariant
- DeepVariant quick start
- DeepVariant via Docker
- DeepVariant whole genome case study
- DeepVariant exome case study
- DeepVariant usage guide
- DeepVariant model training
For technical details describing how DeepVariant works please see our preprint.
Briefly, we started with GIAB reference genomes, for which there is high-quality ground truth available. Using multiple replicates of these genomes, we produced tens of millions of training examples in the form of multi-channel tensors encoding the sequencing instrument data, and then trained a TensorFlow-based image classification model (inception-v3) to assign genotype likelihoods from the experimental data produced by the instrument. Read additional information on the Google Research blog.
The Genomics team in Google Brain actively supports DeepVariant and are always interested in improving the quality of DeepVariant. If you run into an issue, we recommend you follow one of two approaches to getting the issue resolved.
If you have found a bug in DeepVariant - i.e., the code itself needs to be fixed - please report the problem on our Issue tracker. Make sure to add enough detail to your report that we can reproduce the problem and fix it. We encourage including links to snippets of BAM/VCF/etc. files that provoke the bug, if possible. Depending on the severity of the issue we may patch DeepVariant immediately with the fix or roll it into the next release.
If you have general questions about DeepVariant usage, please post your question to BioStars, adding the tag 'deepvariant'. We monitor BioStars posts tagged with DeepVariant and will respond as needed there.
Interested in contributing? See CONTRIBUTING.
DeepVariant is licensed under the terms of the BSD-3-Clause license.
DeepVariant happily makes use of many open source packages. We'd like to specifically call out a few key ones:
We thank all of the developers and contributors to these packages for their work.
- This is not an official Google product.