deepvariant
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google
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
**ISSUE** First of all, I found DeepVariant to be a very good and innovative tool. I'm considering including it in my exome analysis pipeline. I followed the tutorial (DeepVariant worked...
Hi, I am opening this issue to follow up an issue already mentioned here https://github.com/google/deepvariant/issues/366 regarding calling of variants in the initial and last bases of the human mitochondria. Wanted...
Hi All, When using the DeepVariant model type ONT_R104, does it also call structural variants (SVs), specifically ones between 0 and 30bp in length? We observe tools such as Sniffles...
Hello, some of you might remember me. I know Deepvariant works well in human and in some species like rice, if I recall well. In short, all species with (very)...
I’m new to working with computers tools like DeepVariant. I’m trying to build DeepVariant using Docker on a Mac M1 and am encountering issues with the Dockerfile during the Bazel...
Dear Deepvariant devolopers, I am currently working on a Pacibio Hifi dataset from a non-model species. Unfortunately, there is no existing trio hifi dataset for a accurate training. However, we...
I noticed a small typo in the file `docs/deepvariant-details.md` on the first line. The current text is: ``` f# DeepVariant usage guide ``` It would be better to remove the...
Hello, Sorry for writing again about some questions in the analysis, I don't have any expertise on DeepVariant/variant benchmarking around me :( I wanted to benchmark identified variants using hap.py...
Hi, Here is a set of additional parameter I used in 'make_examples' step to create examples for retraining DeepVariant: --min_base_quality 5 \ --min_mapping_quality 1 \ --vsc_min_fraction_snps 0.02 \ --p_error 0.1...
ATAC-seq
Hi! Any advice for running deepvariant on single-cell ATAC-seq data? I assumed RNA-seq would be most similar but that is still quite different. Thanks!
