Chapter 1 Introduction

This webbook contains all the code used for data analysis in study of the population-level metagenomic data of Podarcis muralis lizards across elevational gradients in various mountain ranges of the Pyrenees.

1.1 Prepare the R environment

1.1.1 Environment

To reproduce all the analyses locally, clone this repository in your computer using:

RStudio > New Project > Version Control > Git

And indicating the following git repository:

https://github.com/alberdilab/elevational_hologenomics.git

Once the R project has been created, follow the instructions and code chunks shown in this webbook.

1.1.2 Libraries

The following R packages are required for the data analysis.

# Base
library(R.utils)
library(knitr)
library(tidyverse)
library(devtools)
library(tinytable)
library(broom.mixed)
library(rmarkdown)

# For tree handling
library(ape)
library(phyloseq)
library(phytools)

# For plotting
library(ggplot2)
library(ggrepel)
library(ggpubr)
library(ggnewscale)
library(gridExtra)
library(ggtreeExtra)
library(ggtree)
library(ggh4x)
library(UpSetR)
library(mapproj)
library(ggpmisc)
library(aplot)

# For statistics
library(spaa)
library(vegan)
library(Rtsne)
library(geiger)
library(hilldiv2)
library(distillR)
library(Hmsc)
library(corrplot)
library(pairwiseAdonis)
library(nlme)
library(lme4)
library(emmeans)

  1. University of Copenhagen, ↩︎

  2. University of Copenhagen, ↩︎

  3. University of Valencia, ↩︎

  4. Centre National de la Recherche Scientifique, ↩︎

  5. University of Valencia, ↩︎

  6. Centre National de la Recherche Scientifique, ↩︎

  7. University of Lund, ↩︎

  8. University of Lund, ↩︎

  9. Aarhus University, ↩︎

  10. University of Copenhagen, ↩︎