Conference Program Home
  My Program

All Times EDT

Legend:
CC = Walter E. Washington Convention Center   M = Marriott Marquis Washington, DC
* = applied session       ! = JSM meeting theme

Activity Details

524 Thu, 8/11/2022, 8:30 AM - 10:20 AM CC-204A
Recent Advances in Methods for Genomic Data Analysis — Contributed Papers
Section on Statistics in Genomics and Genetics
Chair(s): Anna Plantinga, Williams College
8:35 AM Neural Network Models for Sequence-Based TCR and HLA Association Prediction
Si Liu, Fred Hutchinson Cancer Research Center; Phil Bradley, Fred Hutchinson Cancer Research Center; Wei Sun, Fred Hutchinson Cancer Research Center
8:50 AM Estimating Cell-Type-Specific Gene Co-Expression Networks from Bulk Gene Expression Data with an Application to Alzheimer's Disease
Chang Su, Yale University; Emma Jingfei Zhang, University of Miami; Hongyu Zhao, Yale University
9:05 AM Identifying Differentially Methylated CpG Sites and Regions Based on the Generalized Beta Distribution
Chengzhou Wu, University of Memphis; Xichen Mou, University of Memphis; Hongmei Zhang, University of Memphis
9:20 AM A General Framework for Powerful Confounder Adjustment in Omics Association Studies
Asmita Roy, Texas A&M University; Xianyang Zhang, Texas A&M university
9:35 AM High-Dimensional Mean Vector Test for One-Sided Hypothesis
Rongrong Wang, Division of Biostatistics and Data Science Medical College of Georgia Augusta University ?; Deepak Nag Ayyala, Division of Biostatistics and Data Science Medical College of Georgia Augusta University ?; Santu Ghosh, Division of Biostatistics and Data Science Medical College of Georgia Augusta University ?
9:50 AM Ensembling for Unsupervised Learning with Application to False Discovery Rates
Jenna Michelle Landy, Harvard T.H. Chan School of Public Health; Giovanni Parmigiani, Dana Farber Cancer Institute
10:05 AM BBQ: Better Base Qualities for Next-Generation Sequencing
Wenyu Gao, Harvard University; Jeffrey Miller, Harvard TH Chan School of Public Health; Robert Klein, Department of Data Science, Dana-Farber Cancer Institute; Philipp Hähnel, Department of Data Science, Dana-Farber Cancer Institute; Scott Carter, Department of Data Science, Dana-Farber Cancer Institute