基本信息
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Bio
Chad Shaw is trained as a mathematical statistician, and he has worked in statistical genomics and bioinformatics for approximately 20 years. He is currently a Professor at BCM and Adjunct Professor of Statistics at Rice University. He is also the Senior Director of Innovation at Baylor Genetics Laboratory.
He has experience in next-generation sequencing, variant analysis, multi-omic data integration, gene expression profiling and variant functionalization. He also has expertise in copy-number analysis and has worked in the area of mechanistic studies of structural variation, with a focus on the role of repetitive elements in new mutations.
He led the development and analysis of an applied probabilistic model for the transmission of new mutations in the context of human genetic disease, which led to the elucidation of the dependency of recurrence risk on parent of origin, parental somatic mosaicism and paternal age. This fundamental contribution to human genetics was featured in many reviews and in the New York Times as a lay press article.
He has been an author on approximately 200 peer-reviewed publications, and his work has been cited approximately 17,000 times. He has trained 5 Ph.D. students in his own laboratory and over 10 students as a thesis committee member. He serves as chairman of the qualifying exam committee for the Quantitative and Computational Biosciences program. His students have performed methodologic research in high dimensional sparse regression, statistical methods for high throughput NGS screens approaches to modifiers of Mendelian disease, eQTL analyses and software tools for variant prioritization in rare disease diagnostics.
He has experience in next-generation sequencing, variant analysis, multi-omic data integration, gene expression profiling and variant functionalization. He also has expertise in copy-number analysis and has worked in the area of mechanistic studies of structural variation, with a focus on the role of repetitive elements in new mutations.
He led the development and analysis of an applied probabilistic model for the transmission of new mutations in the context of human genetic disease, which led to the elucidation of the dependency of recurrence risk on parent of origin, parental somatic mosaicism and paternal age. This fundamental contribution to human genetics was featured in many reviews and in the New York Times as a lay press article.
He has been an author on approximately 200 peer-reviewed publications, and his work has been cited approximately 17,000 times. He has trained 5 Ph.D. students in his own laboratory and over 10 students as a thesis committee member. He serves as chairman of the qualifying exam committee for the Quantitative and Computational Biosciences program. His students have performed methodologic research in high dimensional sparse regression, statistical methods for high throughput NGS screens approaches to modifiers of Mendelian disease, eQTL analyses and software tools for variant prioritization in rare disease diagnostics.
Research Interests
Papers共 336 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
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期刊级别
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Catherine C. Bradley,Chen Wang,Alasdair J. E. Gordon, Alice X. Wen,Pamela N. Luna, Matthew B. Cooke,Brendan F. Kohrn,Scott R. Kennedy,Vasanthi Avadhanula,Pedro A. Piedra,Olivier Lichtarge,Chad A. Shaw,
JOURNAL OF PEDIATRIC GENETICSno. 01 (2024): 29-34
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCEno. 3 (2024): 25-25
Ryan J. Taft,Erin Thorpe, Taylor Williams,Chad A. Shaw, Evgenii Chekalin,Julia Ortega,Keisha D. Robinson, Jason Button,Marilyn C. Jones,Miguel del Campo,Donald Basel,Julie McCarrier,
Research Square (Research Square) (2023)
Genetics in Medicine Open (2023): 101830
Blood (2023): 1296
Ryan Taft,Erin Thorpe,John Belmont, Taylor Williams,Chad Shaw, Jason Button,Julia Ortega,Keisha Robinson,Marilyn Jones,Diane Masser-Frye,Donald Basel,Chester Brown,
Genetics in Medicine Openno. 1 (2023): 100464-100464
crossref(2023)
iScienceno. 9 (2023): 107596-107596
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Author Statistics
#Papers: 340
#Citation: 26748
H-Index: 85
G-Index: 85
Sociability: 8
Diversity: 4
Activity: 17
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