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Activity Number:
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1
- Invited E-Poster Session
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Type:
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Invited
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Date/Time:
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Sunday, August 2, 2020 : 12:30 PM to 3:30 PM
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Sponsor:
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Biometrics Section
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Abstract #313833
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Title:
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Addressing Measurement Error in Microbiome Data
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Author(s):
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David Clausen* and Amy Willis
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Companies:
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Department of Biostatistics, University of Washington and Department of Biostatistics, University of Washington
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Keywords:
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Microbiome;
Calibration;
Measurement error
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Abstract:
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Next-generation sequencing methods such as 16S amplicon sequencing and shotgun metagenomics have allowed an unprecedented view into the structure of microbial communities. However, these methods are known to suffer from substantial bias, with estimates of community composition strongly depending on laboratory protocol (McLaren et al., 2019). To address this problem, we propose a multinomial-normal model that estimates bias via measurements on specimens of known composition and uses this information to calibrate measurements taken on other specimens. We evaluate the performance of this model via simulation as well as on several publicly available microbiome datasets.
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Authors who are presenting talks have a * after their name.
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