American Statistical Association New York City Metropolitan Area Chapter The Levin Lecture Series Department of Biostatistics Colloquium Columbia University

Sequencing studies, such as targeted, whole exome and whole genome sequencing studies, are increasingly being conducted to identify rare variants that are associated with complex traits. Design and analysis of such population based sequencing association studies face many challenges. The talk has three parts. I will first provide an overview of several methods for studying rare variant effects, including burden tests, SKAT and optimal unified tests. Analysis pipelines for whole exome sequencing association studies, such as filtering criteria and small sample adjustments of statistical methods, will be discussed. In the second part of the talk, I will discuss designs of sequencing association studies, such as sample size and power calculations, and pros and cons of extreme phenotype sampling and analysis strategies for extreme phenotype sequencing studies. In the last part of the talk, I will discuss the performance of imputation using GWAS data for studying rare variants effects. Simulation studies and real data will be used to illustrate the results.

Xihong Lin is Professor of Biostatistics and Coordinating Director of the Program in Quantitative Genomics at the Harvard School of Public Health. Her group's major research interests lie in development and application of statistical and computational methods for analysis of high-dimensional genomic and 'omics data in population and clinical sciences, and for analysis of correlated data, such as longitudinal, clustered and spatial data. They are interested in statistical genetics and genomics, genetic and epigenetic epidemiology, genes and environment and medical genomics. Current research projects include genome-wide association studies, next generation sequencing studies, gene-environment interactions, and genome-wide DNA methylation studies, pathway analysis and network analysis, proteomics.