Y
Yuya Kobayashi
Researcher at Stanford University
Publications - 37
Citations - 2114
Yuya Kobayashi is an academic researcher from Stanford University. The author has contributed to research in topics: Genetic testing & Medicine. The author has an hindex of 11, co-authored 29 publications receiving 1655 citations. Previous affiliations of Yuya Kobayashi include Shinshu University.
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Journal ArticleDOI
Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria
Keith Nykamp,Michael J. Anderson,Martin Powers,John Garcia,Blanca Herrera,Yuan-Yuan Ho,Yuya Kobayashi,Nila Patil,Janita Thusberg,Marjorie Jody Westbrook,Scott Topper +10 more
TL;DR: Sherloc builds on the strong framework of 33 rules established by the ACMG–AMP guidelines and introduces 108 detailed refinements, which support a more consistent and transparent approach to variant classification.
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Clinical Evaluation of a Multiple-Gene Sequencing Panel for Hereditary Cancer Risk Assessment
Allison W. Kurian,Emily E. Hare,Meredith A. Mills,Kerry Kingham,Lisa A. McPherson,Alice S. Whittemore,Valerie McGuire,Uri Ladabaum,Yuya Kobayashi,Stephen E Lincoln,Michele Cargill,James M. Ford +11 more
TL;DR: Results suggest that multiple-gene sequencing may benefit appropriately selected patients, and additional studies are required to quantify the penetrance of identified mutations and determine clinical utility.
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Clinical Actionability of Multigene Panel Testing for Hereditary Breast and Ovarian Cancer Risk Assessment.
Andrea Desmond,Allison W. Kurian,Michele Gabree,Meredith A. Mills,Michael J. Anderson,Yuya Kobayashi,Nora Horick,Shan Yang,Kristen M. Shannon,Nadine Tung,James M. Ford,Stephen E Lincoln,Leif W. Ellisen +12 more
TL;DR: In a clinically representative cohort, multigene panel testing for HBOC risk assessment yielded findings likely to change clinical management for substantially more patients than does BRCA1/2 testing alone.
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DNA methylation profiling reveals novel biomarkers and important roles for DNA methyltransferases in prostate cancer
Yuya Kobayashi,Devin Absher,Zulfiqar Gulzar,Sarah R. Young,Jesse K. McKenney,Donna M. Peehl,James D. Brooks,Richard M. Myers,Gavin Sherlock +8 more
TL;DR: This study quantitatively profiled 95 primary prostate tumors and 86 benign adjacent prostate tissue samples for their DNA methylation levels at 26,333 CpGs representing 14,104 gene promoters by using the Illumina HumanMethylation27 platform and identified 87CpGs that are the most predictive diagnostic methylation biomarkers of prostate cancer.
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Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation
TL;DR: The observations made in this study suggest that, with certain caveats, a very low allele frequency threshold can be adopted to more accurately interpret sequence variants.