Wavelet-Based Microbiome Correlations of Host Traits

Abstract

The gut microbiome is composed of a plethora of microorganisms, and these microbes contribute to overall human health. It has been shown that dysbiosis of the microbiome is associated with certain diseases, including colorectal cancer and diabetes, yet the role of the microbiome is still little-known. Here, we aim to develop a novel wavelet-based framework to dissect the microbiome correlations of host traits. Due to the clinical nature of the biological dataset, we utilize the discrete wavelet transform (DWT)—enabling us to impute sparse matrices and decompose the data into different frequency components. We further carry out regressions of host traits with the microbiome relative abundances followed by computing correlations between the regression-predicted trait values. Moreover, we visualize these microbiome correlations of host traits with heat maps and build microbiome correlations of host traits network. As a result, our results revealed that microbiome correlations of host traits are prevalent. Our wavelet-based microbiome correlations of host traits analytic framework aims to lay the foundation for further causality analysis of the complex interplays between the microbiome and host traits.