Differential Gene Expression Analysis

Statistical analyses were performed mainly using the R packages, including ade4 ggplot2, (http://www.r‐project.org/), together with Python (Sanner, 1999 ), Canoco for Windows 4.5 (Microcomputer Power), and PAST (Hammer et al., 2001 ). Differences in the relative abundances of taxonomic groups between samples at gene level were evaluated using a Mann–Whitney test. False discovery rate (FDR) values were estimated using the Benjamini–Yekutieli method to control for multiple testing (Benjamini & Yekutieli, 2001 (link)). p‐values <.05 were considered statistically significant. Differentially expressed genes were identified using DESeq2 (Love et al., 2014 (link)).