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144 * !
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Tue, 8/10/2021,
10:00 AM -
11:50 AM
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Virtual
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Biases, Batch Effects, and Novel Statistical Methodologies: Handling Them in Large-Scale Microbiome Sequencing Studies — Invited Papers
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ENAR, Biometrics Section, Canadian Statistical Sciences Institute
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Organizer(s): Ni Zhao, Johns Hopkins University
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Chair(s): Anna Plantinga, Williams College
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10:05 AM
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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
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10:25 AM
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Bias-Robust Analysis of Microbiome Data
Glen Satten, Emory University
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10:45 AM
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Differential Abundance Analysis of Microbiomes with Bias Correction
Shyamal Peddada, The Eunice Kennedy Shriver National Institute of Child Health and Human Development
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11:05 AM
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BugSigDB: A Database of Published Microbial Signatures
Levi Waldron, CUNY Graduate school Public Health and Health Policy
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11:25 AM
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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
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11:45 AM
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Floor Discussion
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