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Activity Number:
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432
- Novel Statistical Methods for Microbiome Data Analysis
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Type:
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Topic-Contributed
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Date/Time:
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Thursday, August 12, 2021 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistics in Genomics and Genetics
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Abstract #317316
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Title:
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Meta-Analysis of Microbiome Studies for Selecting Disease-Associated Microbial Signatures
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Author(s):
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ZhengZheng Tang*
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Companies:
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University of Wisconsin-Madison
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Keywords:
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meta-analysis;
microbiome;
compositional data;
variable selection;
summary statistics
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Abstract:
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Meta-analysis that synthesizes information across multiple studies is increasingly important in microbiome research to discover generalizable microbial signatures for the disease of interest. Here we introduce a new method named MetaMic for meta-analysis of microbiome association studies. Simulation studies and real data analysis reveal that MetaMic properly accommodates the unique features of microbiome data and boosts the accuracy of microbial signature selection.
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Authors who are presenting talks have a * after their name.
