---
title: "Start R -- First steps with R and RStudio"
author: "Claire Vandiedonck & Jacques van Helden"
date: "`r Sys.Date()`"
output:
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subtitle: DUBii -- Statistics with R
font-family: Garamond
transition: linear
---

```{r include=FALSE, echo=FALSE, eval=TRUE}
library(knitr)

options(width = 300)
knitr::opts_chunk$set(
  fig.width = 7, fig.height = 5, 
  out.width = "80%",
  fig.align = "center", 
  fig.path = "figures/start-R_",
  size = "tiny", 
  echo = TRUE, 
  eval = TRUE, 
  warning = FALSE, 
  message = FALSE, 
  results = TRUE, 
  comment = "")
# knitr::asis_output("\\footnotesize")

# dir.main <- "~/stat1"
# dir.slides <- file.path(dir.main, "slides")
# setwd(dir.slides)
```



## Connection to IFB RStudio server

In a Web browser, open a connection to the IFB RStudio server

<https://rstudio.cluster.france-bioinformatique.fr/>

This requires your login and password. 

Check the version of R and of loaded packages.
```{r eval=TRUE}
## Print info about the session
sessionInfo()

```



## Navigating in your folders


### Where am I?

```{r eval=FALSE}
## Where am I now?
getwd()

## Where is my home?
Sys.getenv("HOME")

## Who am I?
Sys.getenv("LOGNAME")

## Go home
setwd(Sys.getenv("HOME"))
setwd("~")  ## An easier way

```

### Explanations

- `Sys.getenv()` returns all the environment variables
- `$HOME` is a Unix variable environment indicating the home directory
- `$LOGNAME` is my login name (did you guess?)
- in Unix, `~` denotes your home directory (equivalent to `$HOME`)


## Defining a specific directory for this session

We will create a specific directory to store the data and results of the practicals for this course.
For this we use the function `file.path()` to concatenate subfolders. 

```{r eval=FALSE}
## Define the directory for this course
courseDir <- file.path("~", "dubii20", "stat-R", "session1")
print(courseDir) ## Check the result

```


## Creating a directory for this session

Use the command `dir.create()` to create the directory defined`courseDir` defined in the previous slide. 

```{r eval=FALSE}
## Create the directory
dir.create(courseDir) ## THIS WILL LIKELY NOT WORK
```

The above command returned an error. Do you understand why?
If not read the help page and find a way to solve the problem. 

```{r}
help(dir.create )
```


## Creating a directory for this session

**Solution:**

- The command `dir.create()` refused to create a subdirectory (`session1`) because its parent directories (`dubii2020` and `stat-R`) did not exist.
- We can use the option `recursive= TRUE` to create.

```{r eval=FALSE}
## Create the directory with the recursive option
dir.create(path = courseDir, recursive = TRUE)
```
Now, re-run the same command and check the result. 


```{r eval=FALSE}
## Create the directory with the recursive option
dir.create(path = courseDir, recursive = TRUE)
```

## Creating a directory for this session

```{r eval=FALSE}
## Create the directory with the recursive option
dir.create(path = courseDir, 
           recursive = TRUE, ## Create the parent directories
           showWarnings = FALSE) ## Don't shout it already exists

## Go to this directory
setwd(courseDir)
getwd() ## Check that you are in the right place
```



## Load the data for this course

Data and files are stored on the cluster in the directory `/shared/projects/dubii2020/data/module3/seance1/`

We will download the data `Prerequis.RData`  that you saved during the prerequisites session.

```{r eval=FALSE}
## Define the path of the files
data_path <- "/shared/projects/dubii2020/data/module3/seance1/"
print(data_path) ## Check the result

## Load the data from this path
load(paste(data_path, "Prerequis.RData", sep=""))

## List the data you have dowloaded, check their struture and keep in your session only the three vectors called size, weight and bmi as well as the matrix called myData2
ls()

## to complete on your own with `rm()`

```

Finally, open the script `DUBii_R_Session1.R` stored in the same directory as the data.