Clinical OMICS

JAN-FEB 2018

Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine

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Page 34 of 51 January/February 2018 Clinical OMICs 33 Looking to significantly reduce the error rate inherent in the assembly of genomes using high-throughput sequenc- ing (HTS) methods, Google recently launched DeepVari- ant, a deep-learning technology that its creators contend will "reconstruct the true genome sequence from HTS data." "DeepVariant is the first of what we hope will be many contributions that leverage Google's computing infrastruc- ture and ML expertise to both better understand the genome and to provide deep learning–based genomics tools to the community," wrote Mark DePristo, Ph.D., (who built GATK while at the Broad Institute), and Ryan Poplin of the Google Brain Team, in a blog post. Development of the tool took roughly two years and was a collaboration between Google Brain and sister Alphabet company Verily Life Sciences. The problem the DeepVariant team sought to solve is the error rates inherent in the 100-base short reads of HTS, which can range anywhere from 0.1% to as high as 10%. To do this, the developers at Google eschewed the more com- mon statistical methods of variant calling to instead perform this reconstruction using image classification, leveraging the company's expertise in using neural networks for image recognition. To help "train" DeepVariant, the Google team used ref- erence genomes from the Genome in a Bottle Consortium. "Using multiple replicates of these genomes, we pro- duced tens of millions of training examples in the form of multi-channel tensors encoding the HTS instrument data, and then trained a TensorFlow-based image classification model to identify the true genome sequence from the exper- imental data produced by the instruments," DePristo and Poplin wrote. Using this visual approach, DeepVariant can automatically identify small insertions and deletions, and single-base-pair mutations from raw sequencing data. A year ago, DeepVariant won the award for the highest SNP accuracy at the precisionFDA Truth Challenge. This despite the fact the tool had no specific or specialized knowl- edge of genomics and HTS. Since then, the development team has continued to train the system and has decreased the variant calling error rate by another 50%. DeepVariant is being made available to the genomics community as an open-source tool on the Google Cloud Platform. For co-developer Verily Life Sciences, the tool promises to play a significant role in the company's ongoing clinical studies, notably Project Baseline, a collaboration with Duke University School of Medicine and Stanford Medicine. Proj- ect Baseline will recruit 10,000 people to participate in a one of the broadest longitudinal studies of human health, one that will collect medical information, genomic data, and patient-generated health and behavioral data in an effort to more precisely understand the nature of health and disease development. "With recent advances at the intersection of science and technology, we have the opportunity to characterize human health with unprecedented depth and precision," said Jes- sica Mega, M.D., chief medical officer of Verily, at its launch earlier this year. "The Project Baseline study is the first step on our journey to comprehensively map human health." Some in the research community, however, feel the team at Google has overhyped their accom- plishments with Deep- Variant. Noted genomic researcher Steven Sal- zberg, Ph.D., of Johns Hopkins chided both the researchers and members of the press in a piece pub- lished in Forbes titled "No, Google's AI Program Can't Build Your Genome Sequence" for what he saw as overhyping the new tool: "Genomics is indeed making great progress, and although I applaud Google for dedicating some of its own scientific efforts to genomics, it's not helpful to exaggerate what they've done so far." — Chris Anderson Google's AI Tool DeepVariant Promises Significantly Fewer Genome Errors Monsitj / Getty Images

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