Martin-Bideguren et al. 2025
1
Introduction
1.1
Prepare the R environment
1.1.1
Environment
1.1.2
Libraries
2
Prepare data
2.1
Load data
2.1.1
Sample metadata
2.1.2
Read counts
2.1.3
Genome taxonomy
2.1.4
Genome base hits
2.1.5
Genome tree
2.1.6
Genome annotations
2.2
Create working objects
2.2.1
Filter reads by coverage
2.2.2
Transform reads into genome counts
2.3
Prepare color scheme
2.4
Wrap working objects
3
Data summary
4
Data statistics
4.1
Sequencing reads statistics
4.2
Sequencing depth
4.3
DNA fractions
4.4
Recovered microbial fraction
5
MAG catalogue
5.1
Genome phylogeny
5.2
Genome quality
5.3
Functional overview
5.4
Functional ordination
5.5
MAGs shared across transects
6
Community composition
6.1
Taxonomy overview
6.1.1
Stacked barplot
6.1.2
Phylum relative abundances
6.2
Taxonomy boxplot
6.2.1
Family
6.2.2
Genus
7
Diversity analyses
7.1
Alpha diversity
7.1.1
Regression plots per transect
7.1.2
Mixed models per metric
7.2
Beta diversity per individual
7.2.1
NMDS across transects and elevational gradient
7.2.2
Spatial distance decay in neutral beta diversity
7.3
Beta diversity per population
7.3.1
Transit zones
8
HMSC set-up
8.1
Load data
8.2
Subsetting
8.3
Define formulas of the Hmsc model
8.4
Define and Hmsc models
8.5
Define MCMC
8.6
Generate Hmsc executables
8.7
Fit Hmsc models (in Mjolnir HPC)
8.8
Assess chain convergence
9
Elevation HMSC analysis
9.1
Load data
9.2
Compute variance partitioning
9.3
Model fit
9.4
Phylogenetic signal
9.5
Elevation predictions
9.5.1
Predicted adundance at elevational level
9.5.2
Responses to elevation
9.6
Functional predictions
9.6.1
Element level
9.6.2
Functional level
9.6.3
Domain level
10
Diet
10.1
Load data
www.alberdilab.dk
www.earthhologenome.org
www.holo-omics.science
AlberdiLab | Martin-Bideguren et al. 2025
Chapter 10
Diet
10.1
Load data
