A Predictive Framework for Integrating Disparate Genomic Data Types Using Sample-Specific Gene Set Enrichment Analysis and Multi-Task Learning

Open Access

Peer-reviewed

Research Article

Brian D. Bennett,

Affiliations Departments of Statistical Science, Computer Science, and Mathematics, Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina, United States of America, Department of Genetics, Department of Biology, Lineberger Comprehensive Cancer Center, and Carolina Center for Genome Sciences, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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Qing Xiong,

Affiliation Department of Genetics, Department of Biology, Lineberger Comprehensive Cancer Center, and Carolina Center for Genome Sciences, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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Sayan Mukherjee ,

Contributed equally to this work with: Sayan Mukherjee, Terrence S. Furey

* E-mail: sayan@stat.duke.edu (SM); tsfurey@email.unc.edu (TSF)

Affiliation Departments of Statistical Science, Computer Science, and Mathematics, Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina, United States of America
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Terrence S. Furey

Contributed equally to this work with: Sayan Mukherjee, Terrence S. Furey

* E-mail: sayan@stat.duke.edu (SM); tsfurey@email.unc.edu (TSF)

Affiliation Department of Genetics, Department of Biology, Lineberger Comprehensive Cancer Center, and Carolina Center for Genome Sciences, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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Breast cancer
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Forecasting
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Gene expression
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Single nucleotide polymorphisms
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Phenotypes
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Genomics
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