This repository contains a series of notebooks and data to reproduce the analyses in Vazquez-Baeza et al. 20XX. However, the sequencing data is not included here, instead we only include processed files (feature tables, metadata tables, phylogenetic tree, etc.). For access to the raw and quality controlled sequences, please refer to Qiita study 11282.
The notebooks are grouped in 6 main sections: normalization, diversity analyses, heatmap visualization, ordination, metric comparison, and environmental classifier.
These notebooks detail how we identified the Acinetobacter that we used for count normalization. Namely taxonomic selection, sequence similarity filtering, normalization, and visualization.
With the normalized count table we proceeded to calculate alpha and beta diversity statistics. Additionally, we use the alpha diversity measurements to compare against the environmental variables.
To visualize the amplicon sequence variants (ASVs), we hierarchically clustered the per-ASV trajectories over the 4 different digesters and represented them as a heatmap.
In order to integrate the microbial and the chemical information, we used a constrained and an unconstrained ordination. In the constrained ordination we use the chemical data, while in the unconstrained ordination we use the phylogenetic information and the microbial data alone.
In order to assess the effect of normalizing the data we computed 5 distance matrices, and compared their normalized and non-normalized versions using Mantel's test.
Lastly, we combined the dataset with a subset of samples from the Earth Microbiome Project (EMP) and created a sample classifier based on the environmental labels from the EMP.
These notebooks were executed with QIIME version 2018.4 and the dependency stack of that release. Except for scikit-bio (0.5.2 at SHA 5665a8909b4) and Emperor (1.0.0 beta16-dev at SHA c9d787ff24).