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

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Authors: Ryan Poplin, Pieter-Chang Chang, David Alexander, Scott Schwartz, Thomas Colthurst, Alexander Ku, Daniel Newburger, et al.
Year: 2017
Journal: Nature Biotechnology
DOI: 10.1038/nbt.4235
Publisher: https://www.nature.com/articles/nbt.4235

Keywords: deepvariant, genomics

Abstract ​

We present DeepVariant a deep convolutional neural network for variant calling from next-generation DNA sequencing data.

Cite this paper ​

@misc{deepvariant2017,
  title  = {A universal SNP and small-indel variant caller using deep neural networks},
  author = {Ryan Poplin, Pieter-Chang Chang, David Alexander, Scott Schwartz, Thomas Colthurst, Alexander Ku, Daniel Newburger, et al.},
  year   = {2017},
  journal = {Nature Biotechnology},
  doi    = {10.1038/nbt.4235},
  url    = {https://doi.org/10.1038/nbt.4235},
}

Source files ​

• [metadata.json](https://raw.githubusercontent.com/badhope/ScholarLib/main/papers/computer-science/Bioinformatics/Genomics/2019-and-earlier/Nature Biotechnology/empirical/bio/deepvariant/metadata.json)
• [paper.bib](https://raw.githubusercontent.com/badhope/ScholarLib/main/papers/computer-science/Bioinformatics/Genomics/2019-and-earlier/Nature Biotechnology/empirical/bio/deepvariant/paper.bib)