Statistical Analysis 16S rRNA and WGS
Samples were clustered using supervised canonical correspondence
analysis (CCA) (including ‘Variable heights’ H1 to H4 as explanatory
variables). The community richness was identified by rarefraction
analysis for each sample using Calypso pipeline (Zakrzewski et al 2016).
Differences in bacterial alpha diversity (Shannon diversity, Richness,
Evenness, Chao & Fischer Alpha) between groups were calculated.
Differentially abundant and significant taxa were evaluated using
Wilcoxon rank test (odds ratio) at a p-value cut off of 0.05 followed by
false discovery rate (FDR) correction of the p value to determine
statistical significance (i.e., p < 0.05/number of tests) for
reproducibility. We also generated quantile – quantile plots (QQ plots)
of the—log (observed p value) versus the—log (expected p values)
within each pair wise comparison for all taxonomic levels and gene
categories to ascertain potentially statistically significant
associations after correction for multiple comparisons.
Beta diversity was calculated using weighted UniFrac distances, whereas,
differences were calculated using Permutational Analysis of Multivariate
Dispersions (PERMDISP2) through the betadisper function. Differences in
the composition of the fecal microbiota between groups were assessed
using the Linear discriminant analysis Effect Size (LEfSe) workflow, by
comparing each height (H2, H3 & H4) to baseline (H1).