# Getting to Know R

### Getting ready for the course

1. Download `Intro_to_R.tar` from `https://ki-data.mit.edu/bcc/teaching/Intro_to_R/` onto Desktop.
2. Un-compress `Intro_to_R.tar` to a folder "Intro\_to\_R"
3. Open RStudio
4. Under the File menu, click on New project, choose Existing Directory
5. Use Browse to locate to the "Intro\_to\_R" folder and then Create Project This will be your working directory for the rest of the day (e.g. \~/Desktop/Intro\_to\_R)
6. Create a new R script (File > New File > R script) and save it in your working directory (e.g. intro\_to\_R.R). Here, you can type all the commands we run during the course, and save it for later reference.

Using R as a calculator

```r
> 1+2
[1] 3
> 1+2*3+4*5
[1] 27
```

R is good at statistics

```r
> group1<-c(4.5,4.7,4.2,4.8,3.9)
> group2<-c(6.0,5.9,5.8,5.5,6.2)
> t.test(group1,group2)

        Welch Two Sample t-test

data:  group1 and group2
t = -7.2281, df = 7.1573, p-value = 0.0001556
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -1.9355112 -0.9844888
sample estimates:
mean of x mean of y 
     4.42      5.88 
```

The R syntax from an example script

```r
# Load libraries
library(Biobase)
library(limma)
library(ggplot2)

# Setup directory variables
baseDir <- getwd()
dataDir <- file.path(baseDir, "data")

# Load data
design_dat <- read.table(file.path(dataDir, 'mouse_exp_design.csv'), header=T, sep=",", row.names=1)

```

```
*The above snippet of R code has many different “parts of speech” for R (syntax):
*the comments # and how they are used to document function and its content
*the assignment operator <-
*variables and functions
*the = for arguments for functions

```


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