Intro to R and R Studio

class: center, middle, title-slide

.title[
# Intro to R and R Studio
]
.author[
### Joseph Elsherbini, remixing Claus O Wilke and Scott Handley
]
.date[
### 01-09-2023
]

---

<br>

.center[
<img src = "intro_to_r_and_rstudio_files\foundational_skills.png", width = 100%></img>
]

---

## What is R?

R is a general purpose programming language that's really well suited to statistics, manipulating tabular data, and plotting.

---

## Why R?

???

The R logo [is distributed](https://www.r-project.org/logo/) under the terms of the Creative Commons Attribution-ShareAlike 4.0 International license ([CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)).

RStudio hex stickers [are distributed](https://github.com/rstudio/hex-stickers) under [CC0.](https://github.com/rstudio/hex-stickers/blob/master/LICENSE.md)

<img src = "intro_to_r_and_rstudio_files/package-hexlogos.svg", width = 35%, style = "position:absolute; top: 5%; left: 55%;"></img>
---

[//]: # "segment ends here"

## Obtaining R

Windows, Mac or Linux OS: https://www.r-project.org

.center[
<img src = "intro_to_r_and_rstudio_files/Rlogo.svg", width = 30%></img>
]
---

# Running R

.pull-left[
## Command line
 - from the command line, just type R
 - interactive session, nothing is saved by default

## Rstudio
- RStudio: http://www.rstudio.com
- Makes working with R much easier, particularly for a new R user
]
.pull-right[
##VSCode
- https://code.visualstudio.com/download
- not a full IDE, but you can customize it with extensions
- Guide on setting up VSCode for R programming: https://renkun.me/2019/12/11/writing-r-in-vscode-a-fresh-start/ and https://renkun.me/2022/03/06/my-recommendations-of-vs-code-extensions-for-r/
]
---

## The first core concept: Markdown

**Input:**

.small-font[
```
This is a sentence in Markdown, containing `code`, **bold text**,
and *italics*.
```
]

**Output:**

.small-font[
This is a sentence in Markdown, containing `code`, **bold text**, and *italics*.
]

---

## The first core concept: Markdown

.pull-left[
**Input:**

.small-font[
```
## 1 Introduction

Data visualization is part art 
and part science. The challenge 
is to get the art right without
getting the science wrong and 
vice versa.
```
]]

.pull-right[
**Output:**

## 1 Introduction

Data visualization is part art 
and part science. The challenge 
is to get the art right without
getting the science wrong and 
vice versa.

]

.absolute-bottom-right[
Text taken from: C. O. Wilke, [Fundamentals of Data Visualization](https://clauswilke.com/dataviz/introduction.html)
]

---

## R Markdown combines Markdown and R code

**Input:**

.small-font[

````
The function `rnorm()` creates normal variates.
```{R}
rnorm(5) # create 5 normal variates
```
````
]

**Output:**

.small-font[

The function `rnorm()` creates normal variates.

```r
rnorm(5) # create 5 normal variates
```

```
[1] -0.5861735 -0.8000169  0.8848258  0.2603640 -0.9689883
```
]

[//]: # "segment ends here"

---

## Using RStudio

If you haven't already, go to https://posit.cloud/content/5195221 and "Save a Permanent Copy"

Then click on "install_for_workshop.R" on the bottom right file viewer, and go to Code -> Source

---
## Using RStudio

.center[
<img src = "intro_to_r_and_rstudio_files/RStudio-clean.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Using RStudio

.center[
<img src = "intro_to_r_and_rstudio_files/RStudio-clean-edited.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Knitting an R Markdown file

.center[
<img src = "intro_to_r_and_rstudio_files/RStudio-markdown.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Knitting an R Markdown file

.center[
<img src = "intro_to_r_and_rstudio_files/RStudio-markdown-edited.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Knitting an R Markdown file

.center[
<img src = "intro_to_r_and_rstudio_files/markdown-knitted.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Knitting to pdf

.center[
<img src = "intro_to_r_and_rstudio_files/RStudio-markdown-edited2.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Knitting to pdf

.center[
<img src = "intro_to_r_and_rstudio_files/markdown-knit-pdf-edited.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Knitting to pdf

.center[
<img src = "intro_to_r_and_rstudio_files/markdown-knitted-pdf.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Knitting to pdf

.center[
<img src = "intro_to_r_and_rstudio_files/markdown-knitted-pdf-edited.png", width = 80%, style = "position:relative; top:-52px;"></img>
]

---

## Further reading

- [R Markdown tutorial](https://rmarkdown.rstudio.com/lesson-2.html)
- [R Markdown cheatsheet](https://github.com/rstudio/cheatsheets/raw/main/rmarkdown.pdf)
- [R Markdown book](https://bookdown.org/yihui/rmarkdown/)

---

# Using R as a calculator

The simplest thing you can do with R is arithmetic

```r
# + - / * for basic arithmetic
# ** for exponents, sqrt, pi, log10, and more
100 + 1
```

```
[1] 101
```

---

## What percentage of your life have you spent in higher education (after grade school) as a student or trainee?

1. Create a new R markdown file (File -> New File -> R Markdown) and delete everything after the first five line header.

2. Create a new chunk by going to Code -> Insert Chunk or hitting Ctrl + Alt + i

3. Make an arithmetic expression to calculate the percentage

```r
10 + 4 # you can add 
10 - 4 # subtract
4 / 2 # divide
2 * 5 # multiply
3 ^ 4 # and exponentiate
# remember PEMDAS!
y <- (3 + 4) * 7 + 3
```

---

# The `tidyverse`

The tidyverse is a collection of packages that all work together to make data science easier and more sensical in R.

---

---

---

---

# What does the tidyverse look like?

```r
my_microbiome_data %>%
  filter(genus == "Streptococcus") %>%
  group_by(sample) %>%
  summarise(total_strep = sum(relative_abundance)) %>%
  my_plotting_function()
```

---
class: center, middle

# the pipe operator `%>%`

---
class: center, middle

# `%>%` is pronounced "and then"

---

# What does the tidyverse look like?

```r
my_microbiome_data %>%
  filter(genus == "Streptococcus") %>%
  group_by(sample) %>%
  summarise(total_strep = sum(relative_abundance)) %>%
  left_join(sample_metadata) %>%
  my_plotting_function()
```

---

# What does the plotting in the tidyverse look like?

```r
# inside the my_plotting_function()
  
data %>%
  ggplot(aes(x = sample_condition, y = total_strep)) +
  geom_boxplot() +
  geom_point(size=2) +
  scale_y_log10("Streptococcus relative abundance")
```

---

# Getting help

You can get help for a function by using `?` in front

```r
?sqrt
```

**CHEATSHEETS!** If there were one take away from today and tomorrow, it'd be to print these and hang them by your desk.

https://posit.co/resources/cheatsheets/

Can also find the cheatsheets from inside RStudio: Help -> Cheat Sheets -> Browse Cheat Sheets

**When googling an R question, add "tidyverse" to your search**

---