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The Department of Biostatistics Presents: Julia Fukuyama, Stanford University
February 8, 2018 @ 3:30 pm - 4:30 pm
1690 SPH I
Julia Fukuyama, Ph.D.
Postdoctoral Research Fellow
Department of Computational Biology
Stanford University
Dimensionality Reduction with Structured Variables and Applications to the Microbiome
Studies of the microbiome, the complex communities of bacteria that live in and around us, present interesting statistical problems. In particular, bacteria are best understood as the result of a continuous evolutionary process and methods to analyze data from microbiome studies should use the evolutionary history. Motivated by this example, I describe adaptive gPCA, a method for dimensionality reduction that uses the evolutionary structure as a regularizer and to improve interpretability of the low-dimensional space. I also discuss how adaptive gPCA applies to general variable structures, including variables structured according to a network, as well as implications for supervised learning and structure estimation.
Light refreshments for seminar guests will be served at 3:10 p.m. in 1690