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20171222 李洪哲:Methods for High Dimensional Compositional Data Analysis with Applications in Microbiome Studies
时间:2017-12-13

题目:Methods for High Dimensional Compositional Data Analysis with Applications in Microbiome Studies

主讲:Hongzhe Li

时间:2017122210:00-11:00

地点:明德主楼1030会议室

 

摘要:Human microbiome studies using high throughput DNA sequencing generate compositional data with the absolute abundances of microbes not recoverable from sequence data alone. In compositional data analysis, each sample consists of proportions of various organisms with a unit sum constraint. This simple feature can lead traditional statistical treatments when naively applied to produce errant results and spurious correlations. In addition, microbiome sequence data sets are typically high dimensional, with the number of taxa much greater than the number of samples. These important features require further development of methods for  analysis of high dimensional compositional data.  This talk presents several latest developments in this area, including methods for estimating the compositions based on sparse count data,  two-sample test for compositional vectors and  regression analysis with compositional covariates.  Several real micobiome studies are used to illustrate these methods and several open questions will be discussed.


简介:Dr. Hongzhe Li is a Professor of Biostatistics and Statistics at the Perelman School of Medicine at the University of Pennsylvania (Penn).  He is the Chair of the Graduate Program in Biostatistics and Director of Center of Statistics in Big Data at Penn. Dr. Li has been elected as a Fellow of the American Statistical Association (ASA), a Fellow of the Institute of Mathematical Statistics (IMS) and a Fellow of AAAS. Dr. Li severed on the Board of Scientific Counselors of the National Cancer Institute of NIH and regularly serves on various NIH study sections. He is currently an Associate Editor of Biometrics, Statistica Sinica and also co-Editor-in-Chief of Statistics in Biosciences. He serves as Chair of the Section on Statistics in Genomics and Genetics of the ASA. Dr. Li’s research has been focused on developing powerful statistical and computational methods for analysis of large-scale genetic, genomics and metagenomics data and high dimensional statistics with applications in genomics.  He has published papers in Science, Nature, Nature Genetics, Science Translational Medicine, JASA, JRSS, Biometrika, etc.