A flexible quasi-likelihood model for microbiome abundance count data

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.

Automated summary

In this article, a flexible model for microbiome count data is proposed. The model is based on a quasi-likelihood framework, which does not assume any specific distribution for the microbiome count but assumes the variance as an unknown but smooth function of the mean. Simulation studies demonstrate that the flexible quasi-likelihood method provides valid inferential results compared to the negative binomial generalized linear model (GLM) and Poisson GLM. The utility of the method is further demonstrated using a real microbiome study on the relationship between adenomas and microbiota. An R package, fql, is provided for applying the method.