DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
DeepVariant-on-Spark is a germline short variant calling pipeline that runs Google DeepVariant on Apache Spark at scale.
Scalable and High Performance Variant Calling on Cluster Environments
Joint variant calling with GATK4 HaplotypeCaller, Google DeepVariant 1.0.0 and Strelka2, coordinated via Snakemake.
Whole genome sequencing analysis pipeline for consumer hardware. 100% local, Docker-powered, free and open source.
Notebooks and examples for DeepVariant on Spark project.
A Snakemake workflow for variant calling with DeepVariant, and optionally joint variant calling using GLnexus.
Synthetic somatic mutation read-generation, variant calling pipelines (DeepVariant & GATK), and benchmarking framework for bioinformatics research.
Workflows for whole-genome/exome sequencing data analysis
Benchmarking parabricks GPU-accelerated tools for GATK and beyond!
Nextflow pipeline for variant discovery from PacBio HiFi reads, with phasing, optional SV/methylation and VEP annotation.
Self-built GPU-accelerated WGS pipeline (NVIDIA Parabricks fq2bam + DeepVariant). Runs on a laptop GPU via Docker or a multi-GPU cluster via rootless Podman. hg38 + T2T, checkpoint-resume.
Pipeline Nextflow DSL2 de variant calling germinal sur chr20, benchmarke contre le truth set GIAB HG002 avec hap.py. GATK, bcftools et DeepVariant compares sur donnees identiques.
A small repo that eases use of google's deepvariant with GWA metastudies about hypertension
Germline variant calling pipeline
KOGO 2026 판지놈(pangenome) 실습 재현 파이프라인과 교육자료 — vg giraffe SV genotyping, pangenome-aware DeepVariant, panacus growth curve
A pangenome-aware variant calling pipeline with model tuning and variant interpretation.
Analyze whole genome sequencing data on consumer hardware with no cloud accounts, subscriptions, or bioinformatics degree needed
Showcase of DeepVariant variant calling with fine-tuning on small genomic datasets. Includes example scripts, notebook, and comparison of pretrained vs fine-tuned models.
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