README.Rmd

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# The GrENE-net evolution experiment 

To find more information, visit [grene-net.org](grene-net.org)
For comments or bugs, moisesexpositoalonso@gmail.com

This folder is an R package to contain all the meta data of the GrENE-net experiment, including sample names, information from participants, sample records from participants, environmental data, and scripts to manipulate and analyze genome sequences
To install the package, you can run:
./build.R
./install


The structure of folders is the following:

The key folders and files needed for the R package are:

-DESCRIPTION
-NAMESPACE
These two describe the package name and dependencies

-R/
All R functions that will be available and loaded. These functions will be accessible to call when the package is installed and loaded via library(grene) in any script
-man/ 
The manual of the package containing descriptions of functions and datasets.
-CPP/
C++ functions that can be accessible to be called from R if loaded via the Rcpp module or sourced via the function Rcpp::sourceCpp()

-data/
The data files that will be loaded together with the package when installed adnd loaded via library(grene). Datasets will be accessible in any script as data("nameofdataset")

-data-raw/
Datasets from this project in raw format which are parsed and then stored in data/
R scripts starting with gen_.R load those raw datasets, clean them, and store them in data/

-data-big-seeds
Sequencing dataset pointers to the Short Read Archive with results of a seed sequencing experiment. These seeds started GrENE-net
Intermediate files of those raw sequencing datasets can be stored here

-data-big-flowers-phase1
Sequencing dataset pointers to the Short Read Archive with results of flower sequencing over the years in different GrENE-net sites
Intermediate files of those can also be stored here

-data-sensors
The environmental sensors, which were read by participants every year and send to the organizers. All the iButton data is stored in the google drive folder:
https://drive.google.com/drive/folders/1-vtLaK1bdWlVSHAYC9cjfkzq06xNIeDi?usp=sharing

-data-worldclim
Datasets from worldclim.org which can be matched with the locations of GrENE-net to extract average climates at those locations

-analyses/
Folder containing R files to conduct analyses, make figures, and result tables

-figs/
Folder containing PDFs of result figures created with scripts in analyses/
-tables/
Folder containing .csv of result tables created with scripts in analyses/


## Installation

You can install the development version of grene from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("moiexpositoalonsolab/grene")
```

## Example

This is a basic example which shows you how to solve a common problem:

```{r example}
#library(grene)
## basic example code
```

What is special about using `README.Rmd` instead of just `README.md`? You can include R chunks like so:

```{r cars}
summary(cars)
```

You'll still need to render `README.Rmd` regularly, to keep `README.md` up-to-date. `devtools::build_readme()` is handy for this. You could also use GitHub Actions to re-render `README.Rmd` every time you push. An example workflow can be found here: <https://github.com/r-lib/actions/tree/v1/examples>.

You can also embed plots, for example:

```{r pressure, echo = FALSE}
plot(pressure)
```

In that case, don't forget to commit and push the resulting figure files, so they display on GitHub and CRAN.