A universal SNP and small-indel variant caller using deep neural networks

By Ryan Poplin, Pi-Chuan Chang, David H. Alexander, Scott Schwartz, Thomas Colthurst, Alexander Ku, Daniel E. Newburger, Jojo Dijamco, Nam D. Nguyen, Pegah T. Afshar and 4 more. 2018

1,463 citations recorded by the source corpus.

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Citations in the corpus

An overview of deep learning in medical imaging focusing on MRI (2018, background): “Not only medical technology companies, but also for example Google Brain [29, 30, 31]5, DeepMind [32]6, Microsoft [33, 34]7 and IBM [35]8.”
Pangenomics enables genotyping known structural variants in 5,202 diverse genomes (2021, background): “DeepVariant is a highly accurate genotyping tool that requires training ( 25 ).”
Next-Generation Sequencing Technology: Current Trends and Advancements (2023, unknown): “Cont.”
Artificial intelligence in clinical and genomic diagnostics (2019, methodology): “DeepVariant, a CNN-based variant caller trained directly on read alignments without any specialized knowledge about genomics or sequencing platforms, was recently shown to outperform standard tools on some variant-calling tasks [54].”
A guide to machine learning for biologists (2021, methodology): “Medical image recognition [24,57] Variable input size”
Artificial Intelligence in Cancer Research and Precision Medicine (2021, background): “Several groups have explored the idea to recast mutation detection as a machine learning problem (33, 34).”
Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome (2019, methodology): “To evaluate variant calling with a deep learning framework, Google DeepVariant 32 was used to call SNVs and indels from CCS reads, with chromosome 20 held out during model training and selection.”
Identifying viruses from metagenomic data using deep learning (2020, background): “…of non-coding variants [24,25], predicting chromatin accessibility [26], calling genetic variants from millions of short reads in NGS samples [27], predicting methylation quantitative trait loci [28], identifying evolutionary conserved sequences [29], and identifying enhancers and promoters…”
Multimodal Large Language Models in Health Care: Applications, Challenges, and Future Outlook (2024, unknown): “Finally, omics encoders (eg, DeepVariant [62], Basenji [63], and DeepCpG [64]) focus on identifying genetic markers or patterns associated with specific diseases, aiding in the development of targeted therapies.”
Haplotype-resolved diverse human genomes and integrated analysis of structural variation (2021, methodology): “Strand-seq data were produced from the same samples and used to identify and phase heterozygous SNVs [LongShot (66) and DeepVariant (67)] from the squashed genome assemblies [Peregrine (68) or Flye (69)].”
A draft human pangenome reference (2022, methodology): “These reference-based call sets were generated from the PacBio HiFi reads and haplotype-resolved assemblies using different discovery methods: DeepVariant (Poplin et al., 2018), PBSV (Pacific Biosciences, 2021), Sniffles (Sedlazeck et al.”