Lab 4: Learning R

class: center, middle, inverse, title-slide

# Lab 4: Learning R
## IGF RNA-Seq Workshop 2017
### Sanzhen Liu
### 6/22/2017

---

### Outline
- Introduction of R

- Data structure (vector and data frame)

- Data importing and exporting

- Plotting

- String operations

---
### Why R?
- R is great at statistical computing and graphics
- R is free
- R has great community supports
***
<div align="center">
<img src="http://129.130.89.83/tmp/public/RNASeq/RNASeq2017/images/Rpopularity.png" width=300 height=400>
</div>

---
### R example 1 (R for statistics)

Chi-square test

```r
d <- c(12, 36, 24, 70)
dm <- matrix(d, nrow=2, byrow=T)
dm
```

```
##      [,1] [,2]
## [1,]   12   36
## [2,]   24   70
```

```r
chisq.test(dm)
```

```
## 
## 	Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  dm
## X-squared = 7.8894e-31, df = 1, p-value = 1
```

---
### R example 2 (R for graphs)

```r
ts="http://129.130.89.83/tmp/public/RNASeq/RNASeq2017/codes/xcard.R"
source(ts)
```

---
### R example 2 code
<div align="center">
<img src="http://129.130.89.83/tmp/public/RNASeq/RNASeq2017/images/xcs.png" width=250 height=500>
</div>

---
### R example 3 (R for graphs)

```r
cs="http://129.130.89.83/tmp/public/RNASeq/RNASeq2017/codes/trend.R"
source(cs)
```

---
### Where can we use R?
**Rstudio** is an open source integrated development environment (IDE) for R

* On your own machine (Rstudio Desktop)
  + Download and install [R](http://cran.r-project.org/mirrors.html)
  + Download and install [Rstudio](https://www.rstudio.com/products/RStudio/)

* Use Rstudio at Beocat (Rstudio server)
  + [rstudio.beocat.cis.ksu.edu](rstudio.beocat.cis.ksu.edu)
  + Your **KSU ID** and **password** to login

---
### Rstudio at Beocat
[rstudio.beocat.cis.ksu.edu](rstudio.beocat.cis.ksu.edu)

---
### Rstudio interface

---
### Getting started, R commands
**Expression**: evaluated, printed, and the value lost

```r
2 + 4
```

```
## [1] 6
```

```r
68 * 0.15
```

```
## [1] 10.2
```

**Assignment** assign values to a variable  
evaluated, the value passed to a variable but NOT printed

_assignment operator_: **<-** or **=**

```r
y <- 2
y = 2
info <- "hello world"
cat(info)
```

```
## hello world
```

---
### Notes
- Comments (#):
Notes to scripts, starting with a hashtag (‘#’), everything to the end of the line is a comment.

y <- 2 + 4  # an example of the assignment

- Variable names are case senstive

```r
y <- 2
Y <- 3
y
```

```
## [1] 2
```

```r
Y
```

```
## [1] 3
```
---
### Executing commands

- PC window: control + return (enter)

- Apple MAC: command + return (enter)

---
### vector: multiple elements
A vector is a single entity consisting of an ordered collection of numbers, characters, logical quantities, etc.

concatenate command: **c()**

- Numeric vector  
  c(10.4, 5.6, 3.1, 6.4, 21.7)
  
- Logical vector   
  c(TRUE, FALSE, TRUE, TRUE)
  
- Character vector  
  c("a", "b", "c")
  
- Missing value (NA, not available)  
  c("a", "b", "c", NA)

---
### vector manipulation - I

```r
# Numeric vector
x <- c(10.4, 5.6, 3.1, 6.4, 21.7)
sum(x)
```

```
## [1] 47.2
```

```r
2*x
```

```
## [1] 20.8 11.2  6.2 12.8 43.4
```

```r
# Logical vector
lv <- c(TRUE, FALSE, TRUE, TRUE)
lv == FALSE
```

```
## [1] FALSE  TRUE FALSE FALSE
```

---
### vector manipulation - II

```r
# Character vector
cv <- c("a", "b", "c")
cv2 <- paste(cv, 1:3, sep="")
cv2
```

```
## [1] "a1" "b2" "c3"
```

```r
# Missing value
mvv <- c("a", "b", "c", NA)
is.na(mvv)
```

```
## [1] FALSE FALSE FALSE  TRUE
```

---
### vector manipulation - III
Vectors must have their values with the same mode, either numeric, character, logical, or other types.

**conversion to other modes**

```r
z <- 0:9
is.numeric(z)
```

```
## [1] TRUE
```

```r
digits <- as.character(z) # convert to character
d <- as.numeric(digits) # convert to numeric
```

---
### vector manipulation - IV
- Select a subset of a vector

```r
x <- c(4, 5, 7, 3, 9)
x[c(2, 3)]
```

```
## [1] 5 7
```

```r
x[x>6]
```

```
## [1] 7 9
```

```r
x[-c(1,5)]
```

```
## [1] 5 7 3
```
- Modify a vector

```r
x[3] <- 23.1
c(x, 10.9)
```

```
## [1]  4.0  5.0 23.1  3.0  9.0 10.9
```

```r
x[-2]
```

```
## [1]  4.0 23.1  3.0  9.0
```

```r
length(x) <- 2  # retain just the first 2 values
x
```

```
## [1] 4 5
```
---
### Question 1
Can a vector contain different types of elements?

```r
c(1, "a")
c(1, TRUE)
c(TRUE, "a")
c(1, "a", TRUE)
```

---
### Data frame
A data frame may be regarded as a matrix (table) with columns possibly of differing modes

- Making data frames

```r
df <- data.frame(name=c("Josh", "rose"), age=c(23, 35))
df
```

```
##   name age
## 1 Josh  23
## 2 rose  35
```

---
### Working with a data frame

```r
df
```

```
##   name age
## 1 Josh  23
## 2 rose  35
```

Trying these commands:

```r
head(df, 1)
tail(df, 1)
str(df)
df[2, 1]
df[2, 2]
df[2]
df[, 2]
```

---
class: center, middle
# 15 min break

---
### Importing data
**read.table()**: to read a data frame (table)  
**read.delim**, **read.csv**

```r
cpm="http://129.130.89.83/tmp/public/RNASeq/RNASeq2017/data/cs.txt"
d <- read.delim(cpm)
head(d, 3)
```

```
##     Date Cost.per.Mb Cost.per.Genome
## 1 Sep-01     5292.39        95263072
## 2 Mar-02     3898.64        70175437
## 3 Sep-02     3413.80        61448422
```

---
### Exporting data
**write.table()** or **write.csv()**

To write a tab-delimited file

```r
x <- data.frame(a = "pi", b = pi)
write.table(x, file="foo.txt", sep="\t", row.names=FALSE)
```

file="foo.txt": foo.txt is the ouput file name
sep="\t": separated by a tab (\t)
row.names=FALSE: row names are not included in the output

---
### Problem
- Create a data frame

three columns: 1. Name 2. Major 3. Gender  
  three rows (entries): your neighbors and you

- Write the data frame to an output file

- Read the file to R and add one more column
(e.g., favorite color)

---
### Plotting: plot()
High-level plot: create a new plot

plot(x, y, xlab, ylab, main, …)

---
### Adding contents to a plot
Low-level plot: add to an existing plot
- add points  
**points()**

- add lines  
**lines()**

- add text or legend  
**text()**  
**legend()**

---
### Scatter plot

```r
area <- state.x77[, "Area"]
pop <- state.x77[, "Population"]
# scatter plot
plot(area, pop, main="US1977")
# label points
points(area["Kansas"], pop["Kansas"], col="purple", lwd=2, pch=19, cex=2)
```

---
### Boxplot

```r
barplot(pop/1000, las=2, cex.names=0.65, ylab="Pop (x1000,000)",
        main="US 1977 Population")
```

---
### Histogram

```r
hist(pop, ylab="Number of states", main="US 1977 Population")
```

---
### String operations - nchar
**nchar()**
nchar the sizes of the corresponding elements of a vector.

```r
cvec <- c("google", "hello", "the", "world")
nchar(cvec)
```

```
## [1] 6 5 3 5
```

---
### String operations - grep
**grep()**
grep searches for matches to argument pattern within each element of a character vector

```r
cvec
```

```
## [1] "google" "hello"  "the"    "world"
```

```r
grep("o", cvec)
```

```
## [1] 1 2 4
```
---
### String operations – sub and gsub
**sub()** and **gsub()**
sub and gsub perform replacement of the first and all matches respectively.

```r
cvec
```

```
## [1] "google" "hello"  "the"    "world"
```

```r
sub("o", "O", cvec)
```

```
## [1] "gOogle" "hellO"  "the"    "wOrld"
```

```r
gsub("o", "O", cvec)
```

```
## [1] "gOOgle" "hellO"  "the"    "wOrld"
```

---
### Package installation
Prepare for Lab 5: RNA-Seq analysis

```r
# DESeq2
source("http://bioconductor.org/biocLite.R")
biocLite("DESeq2")

# GOSeq
biocLite("goseq")

# GO.db
biocLite("GO.db")
```

---
### Getting help
Usage of commands
- help(nchar)
- ?nchar
- ??colsum

[R Reference Card](https://cran.r-project.org/doc/contrib/Short-refcard.pdf)

- [stack overflow](https://stackoverflow.com/)
- [google](https://google.com)

Learning R at [swirlstats](http://swirlstats.com)

---
### Adventure with R
<div align="center">
<img src="http://129.130.89.83/tmp/public/RNASeq/RNASeq2017/images/Radventure.png" width=800 height=500>
</div>
http://www.nature.com/news/programming-tools-adventures-with-r-1.16609

---
### Contact information
Sanzhen Liu  
Plant Pathology  
4022B Throckmorton Plant Sciences Center  
Manhattan, KS 66506-5502  
phone: 785-532-1379

[liu3zhen@ksu.edu](liu3zhen@ksu.edu)  
twitter: [liu3zhen](https://twitter.com/liu3zhen?lang=en)