Setup.Rmd

```{r, setup, include = FALSE, message=FALSE, echo=FALSE}
# library("knitcitations")
library("knitr")
# cite_options(max.names = 3, style = "html", hyperlink = "to.doc")
# bib <- read.bibtex("bibtexlib.bib")
opts_chunk$set(tidy = FALSE, message = FALSE, warning = FALSE, cache = TRUE) 
# use this to set knitr options: 
# http://yihui.name/knitr/options #chunk_options 
library(printr)
```
---
title: "Required Components"
---

This website is an introduction to some of the principles of reproducible 
science in R. While we are using R and other tools for reproducible research, 
our focus here is not to teach you the tools, but how you can use them to make 
your research more reproducible. Before we get started on the bulk of the
content, we will go over how to install the software needed for this tutorial
and briefly introduce working with R.

Installing R and RStudio
-----

First, install R and RStudio:

1. Download and install the [R](http://www.r-project.org) statistical computing
   and graphing environment. This works cross-platform on Windows, OS X and
   Linux operating systems.

2. Download and install the free, open source edition of the [RStudio
   Desktop](https://www.rstudio.com/products/rstudio/download/) integrated 
   development environment (IDE), which we recommend. This is basically a point-and-click
   interface for R that includes a text editor, file browser, and some other conveniences.

Installing the required packages
----

The following packages are used in this primer:

1. [rmarkdown](http://cran.r-project.org/web/packages/rmarkdown/index.html) (creating reports)
1. [agricolae](http://cran.r-project.org/web/packages/agricolae/index.html) (agricultural disease data analysis)
1. [ggplot2](http://cran.r-project.org/web/packages/ggplot2/index.html) (graphs)
1. [poppr](http://cran.r-project.org/web/packages/poppr/index.html) (genetic data analysis)
1. [dplyr](http://cran.r-project.org/web/packages/dplyr/index.html) (data manipulation)
1. [tidyr](http://cran.r-project.org/web/packages/tidyr/index.html) (data manipulation)

To install these packages, open RStudio and copy and paste the following code into the console:

```{r, eval = FALSE}
my_packages <- c("rmarkdown","poppr", "agricolae", "dplyr", "tidyr", "ggplot2")
install.packages(my_packages, repos = "http://cran.rstudio.com", dependencies = TRUE)
```

Congratulations! You should now be all set for using R. To ensure that
everything is set up correctly, you can go through steps 1 and 2 in the
[markdown chapter](Markdown.html).

Optional software
-----------------

### PDFs with LaTeX

If you want to create PDF documents, you will need a
[$\LaTeX$](https://latex-project.org/) installation. 
For OSX and Ubuntu users, this can be a large download and you will want to ensure you have a good connection:

 - [LaTeX for OSX](https://tug.org/mactex/)
 - [LaTeX for Windows](http://miktex.org/)
 - [LaTeX for Ubuntu](https://help.ubuntu.com/community/LaTeX)

To those that know of and fear LaTeX: don't worry, you don't need to write any LaTeX code to produce PDFs from Markdown.

### Git

Git is a version control program that we will cover, but since installation
requirements can vary between operating systems, we are not requiring it for the
workshop. However, if you would like to install it, [Here's a website that
covers installation for the major operating
systems](http://happygitwithr.com/install-git.html). 

A quick introduction to R using RStudio
------------------

Let's review some of the basic features and functions of R. To start R,
open the RStudio application from your programs folder or start menu. This will
initialize your R session. To exit R, simply close the RStudio application.

> Note that R is a case-sensitive language!

Let's get comfortable with R by submitting the following command on the console
(where R prompts you with a `>` in the lower left RStudio window pane) that will
tell you something about your version of R and the packages you have, which is
useful for reporting reproducible research.

```{r, eval = TRUE}
sessionInfo() # This command will tell you information about your current R session
```

> Note that any text after a '#' symbol is a comment and does not affect the code execution;
> you can just type `getwd()` after the ">".

Packages and getting help
-----------------------

One way that R shines above other languages is that R packages in CRAN are all
documented and easy to install. Help files are written in HTML and give the user
a brief overview of:

 - the purpose of a function
 - the parameters it takes
 - the output it yields
 - examples demonstrating its usage

To get help on any R function, type a question mark before the empty function. 
Here's an example of how to get help about the `gather()` function from the
*tidyr* package:

```{r}
library('tidyr') # The package with the gather() function.
?gather          # open the R documentation of the function gather()
```

If you want to run the examples, you can either copy and paste the commands to
your R console, or you can run them all with:

```{r, eval = FALSE}
example("gather", package = "tidyr")
```

Other ways of getting help:

```{r, eval = FALSE}
help(package = "tidyr")  # Get help for a package.
help("gather")           # Get help for the gather function
?gather                  # same as above
??multilocus             # Search for help that has the keyword 'multilocus' in all packages
```

Some packages include vignettes that can have different formats such as being
introductions, tutorials, or reference cards in PDF format. You can look at a
list of vignettes in all packages by typing:

```{r, eval=FALSE}
browseVignettes()                     # see vignettes from all packages
browseVignettes(package = 'poppr')    # see vignettes from a specific package.
```

and to look at a specific vignette you can type:

```{r, eval=FALSE}
vignette('mlg')
```

```{r, echo = FALSE}
detach("package:printr", unload = TRUE)
```