This repository houses the data, code, and related documents associated with our project wherein we investigate the impacts of individual Peromyscus and environmental variation on Lyme disease (Borrelia burgdorferi) risk.
To download this project locally from GitHub, click the green "<> Code" drop down and select "Download ZIP" or clone the git repo.
Some important files that are not related to the analysis are index.Rmd,
render-github-pages.R, and _bookdown.yml, which are responsible for
generating the files in the docs/ folder, which form the
Project GitPages website.
The main project structure is contained in three main sub-folders, documented in the following subsections:
This folder contains data collected from NEON, and the code to acquire and
pre-process it. Data is housed in data/ and code in R/. The R scripts were
executed in sequential order (00 - 03) and depend upon the download-function.R
script. Data are saved as R objects .rds that can be loaded into R with the
readRDS function.
The data/eight_sites/ folder contains data at the eight NEON sites used
by the project. The sub-folders contain data that were downloaded on a per-site
basis (e.g., precipitation/precipitation_BLAN.rds). The bare files are include
data for all sites. Some of these files are created as the result of pre-processing
the raw data.
This folder contains data pertaining to the ibutton-derived capture timing
estimates and code used to process and prepare those data. Data is housed in
data/, code is housed in R/ and grouped into functions/
(R functions created for this project) and scripts, which contains the file
that was used to estimate capture times and depends upon these functions.
The data/ibuttons/ folder contains raw data
(raw-temperatures/, raw-metadata/), cleaned data
(cleaned-metadata/, cleaned-temepratures/), and output from the processing
script.
The capture-time-estimates_2022-2024.rds file contains the combined capture
time estimates from all years of the study.
This is the primary folder of this project involved in data analysis and manuscript preparation. It is grouped into 5 sub-folders:
R: This contains all the code for the project, grouped by functions
(as above, these are R functions that fascilitate the analyses), scripts
(the code used to perform the analyses), and rmarkdown (the documents used
to present information, and create the GitPages website). In general, the
files with numeric prefixes were executed sequentially (e.g., 01-08) and the
other files are standalone (but sometimes depend on output from other files).
data: this is where the data used for this project are stored. The files are
often output from the R code, but also contain raw data seperate from the raw
NEON and activity timing data.
graphical-models contains some preliminary SEM diagrams and graphics
contains figures generated for the manuscript (i.e., via
build-MS-figs-and-tables.R).
manuscript: this is where some of the files associated with manuscript
preparation are stored. But the primary manuscript file is housed
on OneDrive.
To see summaries of our analyses, see our GitPages website.