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DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant is a deep learning-based variant caller that takes aligned reads (in BAM or CRAM format), produces pileup image tensors from them, classifies each tensor using a convolutional neural network, and finally reports the results in a standard VCF or gVCF file. DeepTrio is a deep learning-based trio variant caller built on top of DeepVariant. DeepTrio extends DeepVariant's functionality, allowing it to utilize the power of neural networks to predict genomic variants in trios or duos. See this page for more details and instructions on how to run DeepTrio. Out-of-the-box use for PCR-positive samples and low quality sequencing runs, and easy adjustments for different sequencing technologies and non-human species.
Features
- Out-of-the-box use for PCR-positive samples
- No filtering is needed beyond setting your preferred minimum quality threshold
- DeepVariant can be run via Docker or binaries
- On-premise hardware or in the cloud, with support for hardware accelerators like GPUs and TPUs.
- DeepVariant maintains high accuracy across data from different sequencing technologies
- Easy adjustments for different sequencing technologies and non-human species
Project Samples
