Statistical analyses
Statistical analyses were done either using plugins from Qiime 2.0
v.2021.8 (Bolyen, et al. 2019) environment or in R Statistical Software
(v4.2.1; R Core Team 2021), R: A language and environment for
statistical computing. R Foundation for Statistical Computing, Vienna,
Austria. URL https://www.R-project.org/., using packages Phyloseq
(McMurdie and Susan Holmes 2013), Vegan (Oksanen et al. 2022), Qiime2R
(Bisanz 2018), Microbiomeutilities (v1.0.16, Shetty et Lahti 2022), R
package version 1.00.16., microViz (v0.9.7, Barnett et al. 2021),
MicrobiomeStat (v1.1, Zhang et Chen 2022), MicrobiomeMarker (v1.2.2, Cao
et al. 2022) and ANCOMBC (v1.6.3, Lin et Peddada 2020). Alpha diversity
indices including Chao1, observed ASVs, shannon and simpson as well as
beta diversity indices including bray-curtis, jaccard, weighted and
unweighted unifrac were calculated using plugin diversity and
corresponding pipelines from Qiime 2 and significant differences between
groups were assessed for both groups of indices. Significance in beta
diversity differences among groups was assessed by adonis PERMANOVA
test. Furthermore, dispersion of beta diversity differences within
groups was assessed by the permdisp method. All of the mentioned
analyses were performed in Qiime 2. Ancom analysis to identify
differentially abundant features was performed in the R environment with
the help of aforementioned R packages.