AlberdiLab | Aizpurua et al. 2024
Functional insights into the effect of feralisation on the gut microbiota of cats worldwide
Last update: 2024-11-23
Chapter 1 Introduction
This webbook contains all the code used for data analysis in study on the recovery of metagenome‑assembled genomes and derived microbial communities from domestic and feral cat faecal samples collected in six countries.
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/domestic_feral_cat_metagenomics.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)
library(broom.mixed)
library(rmarkdown)
library(janitor)
# 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)
# For statistics
library(spaa)
library(vegan)
library(Rtsne)
library(geiger)
library(ANCOMBC)
library(lme4)
library(Hmsc)
library(matrixStats)
library(MuMIn)
#library(MASS)
library(nlme)
library(emmeans)
library(hilldiv2)
library(distillR)
library(pairwiseAdonis)
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