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Assisted Selection of Biomarkers by Linear Discriminant Analysis Effect Size LEfSe in Microbiome Data
Published on: May 16, 2022
A flexible quasi-likelihood model for microbiome abundance count data
Yiming Shi1, Huilin Li2, Chan Wang2
1Division of Biostatistics, Washington University in St. Louis, St. Louis, Missouri, USA.
Abstract:
In this article, we present a flexible model for microbiome count data. We consider a quasi-likelihood framework, in which we do not make any assumptions on the distribution of the microbiome count except that its variance is an unknown but smooth function of the mean. By comparing our model to the negative binomial generalized linear model (GLM) and Poisson GLM in simulation studies, we show that our flexible quasi-likelihood method yields valid inferential results. Using a real microbiome study, we demonstrate the utility of our method by examining the relationship between adenomas and microbiota. We also provide an R package "fql" for the application of our method.
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