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144 * ! Tue, 8/10/2021, 10:00 AM - 11:50 AM Virtual
Biases, Batch Effects, and Novel Statistical Methodologies: Handling Them in Large-Scale Microbiome Sequencing Studies — Invited Papers
ENAR, Biometrics Section, Canadian Statistical Sciences Institute
Organizer(s): Ni Zhao, Johns Hopkins University
Chair(s): Anna Plantinga, Williams College
10:05 AM ConQuR: Batch Effect Correction for Microbiome Data via Conditional Quantile Regression
Wodan Ling, Fred Hutchinson Cancer Research Center; Michael C Wu, Fred Hutchinson Cancer Research Center
10:25 AM Bias-Robust Analysis of Microbiome Data
Glen Satten, Emory University
10:45 AM Differential Abundance Analysis of Microbiomes with Bias Correction
Shyamal Peddada, The Eunice Kennedy Shriver National Institute of Child Health and Human Development
11:05 AM BugSigDB: A Database of Published Microbial Signatures
Levi Waldron, CUNY Graduate school Public Health and Health Policy
11:25 AM Integrative Analysis of Multiple Microbiome Data Sets: Robust Models Against Biases and Batches
Ni Zhao, Johns Hopkins University; Mengyu He, JOHNS HOPKINS UNIVERSITY; Runzhe Li, Johns Hopkins Bloomberg School of Public Health
11:45 AM Floor Discussion