Author

Ryan E. Poplin

Google (United States)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genomics· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:variant calling· 3 Assay:whole-genome sequencing· 3 Approach:deep learning· 2 Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Assay:DNA methylation· 1 Organism:human· 1 Assay:metagenomics· 1

Frequent Co-Authors

Mark A. DePristoiD· 3 shared Cory Y. McLeaniD· 2 shared David H. Alexander· 2 shared Pi-Chuan ChangiD· 2 shared Akosua BusiaiD· 1 shared Alexander Ku· 1 shared Ami Levy‐Moonshine· 1 shared Benjamin M. NealeiD· 1 shared

Activity by Year

2018-2019 · peak 2/yr

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10 top collaborators · 25 mutual co-author links

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3 shared papersGenomics

Mark A. DePristoORCID

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3 papers

Recent·Most cited

A deep learning approach to pattern recognition for short DNA sequences

Akosua Busia, George E. Dahl, Clara Fannjiang, David H. Alexander, Elizabeth H. Dorfman, Ryan E. Poplin, Cory Y. McLean, Pi-Chuan Chang, Mark A. DePristo

A convolutional network trained on 16S reads from 13,838 species reaches within 2.0% of training-set Bayes-optimal species accuracy and usually beats k-mer, alignment and Kraken2 on held-out-species genera.

bioRxiv · Aug 10, 2019 · PreprintBioinformatics✦ In-depth digest

Creating a universal SNP and small indel variant caller with deep neural networks

Ryan E. Poplin, Pi-Chuan Chang, David H. Alexander, Scott Schwartz, Thomas Colthurst, Alexander Ku, Dan Newburger, Jojo Dijamco, Nam Nguyen, Pegah Tootoonchi Afshar, Sam S Gross, Lizzie Dorfman, Cory Y. McLean, Mark A. DePristo

A convolutional network on read-pileup images outperforms hand-built statistical variant callers, won an FDA challenge award for SNPs, learns new sequencing technologies and generalizes to other mammals.

Nature Biotechnology · Sep 24, 2018Peer-reviewedGenomics

Scaling accurate genetic variant discovery to tens of thousands of samples

Ryan E. Poplin, Valentín Ruano-Rubio, Mark A. DePristo, Tim J. Fennell, Mauricio O. Carneiro, Geraldine A. Van der Auwera, David E. Kling, Laura Doyle Gauthier, Ami Levy‐Moonshine, David Roazen, Khalid Shakir, Joel Thibault, Sheila Chandran, Chris Whelan, Monkol Lek, , Eric Banks

Per-sample assembly with gVCF output, followed by joint genotyping, lets GATK HaplotypeCaller scale linearly with cohort size while calling indels more accurately than SAMtools, UnifiedGenotyper or Platypus.

bioRxiv · Jul 24, 2018 · PreprintGenomics✦ In-depth digest