A semiparametric model for between‐subject attributes: Applications to beta‐diversity of microbiome data

• Published in: Biometrics Vol. 78; no. 3; pp. 950 - 962
• Main Authors: Liu, J., Zhang, Xinlian, Chen, T., Wu, T., Lin, T., Jiang, L., Lang, S., Liu, L., Natarajan, L., Tu, J.X., Kosciolek, T., Morton, J., Nguyen, T.T., Schnabl, B., Knight, R., Feng, C., Zhong, Y., Tu, X.M.
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.09.2022
• Subjects: copula; Cross-Sectional Studies; functional response model; Gene sequencing; High-Throughput Nucleotide Sequencing - methods; high‐throughput sequencing; Humans; microbial communities; microbiome; Microbiomes; Microbiota - genetics; Microorganisms; permutational multivariate analysis of variance using distance matrices (PERMANOVA); regression analysis; semiparametric regression; species diversity; Statistical analysis; t-test; U‐statistics‐based generalized estimating equation (UGEE); U-statistics-based generalized estimating equation (UGEE); semiparametric regression; functional response model; copula; high-throughput sequencing; permutational multivariate analysis of variance using distance matrices (PERMANOVA)

The human microbiome plays an important role in our health and identifying factors associated with microbiome composition provides insights into inherent disease mechanisms. By amplifying and sequencing the marker genes in high‐throughput sequencing, with highly similar sequences binned together, we...