基本信息
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个人简介
Kathryn Roeder’s research focuses on developing statistical methods for analysis of genetic and genomic data with an aim to find associations between patterns of genetic variation and complex disease. To solve biologically relevant problems, her team utilizes modern statistical methods such as high dimensional statistics, statistical machine learning, nonparametric methods and networks. Her group developed tools for identifying autism risk genes from de novo mutations and, together with the Autism Sequencing Consortium, they have identified more than one hundred autism risk genes. Roeder’s team has developed some of the key statistical tools for the analysis of whole-genome sequencing data, and these methods have helped interpret the impact of noncoding variants on autism and other neuropsychiatric disorders. A recent focus of her group is developing tools for the analysis of single-cell multi-omic data.
Specific Research Interests
A primary goal of my research group is to develop statistical tools for finding associations between patterns of genetic variation and complex disease. To solve biologically relevant problems, we utilize modern statistical methods such as high dimensional statistics, statistical machine learning, nonparametric methods and networks. Data arises from primarily from Next Generation Sequencing and gene expression arrays. Our methodological work is motivated by our studies of schizophrenia, autism and other genetic disorders.
Specific Research Interests
A primary goal of my research group is to develop statistical tools for finding associations between patterns of genetic variation and complex disease. To solve biologically relevant problems, we utilize modern statistical methods such as high dimensional statistics, statistical machine learning, nonparametric methods and networks. Data arises from primarily from Next Generation Sequencing and gene expression arrays. Our methodological work is motivated by our studies of schizophrenia, autism and other genetic disorders.
研究兴趣
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Genome Biologyno. 1 (2024): 124-124
BMC Bioinformaticsno. 1 (2024): 1-30
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2024)
arxiv(2024)
BIOMETRICSno. 1 (2024)
arxiv(2024)
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Cindy Wen,Michael Margolis,Rujia Dai,Pan Zhang,Pawel F Przytycki, Daniel D Vo,Arjun Bhattacharya,Nana Matoba, Miao Tang,Chuan Jiao,Minsoo Kim,Ellen Tsai,
Science (New York, N.Y.)no. 6698 (2024): eadh0829-eadh0829
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