9.3 Exercise 3. Character vector manipulation

9.3.1 Exercise 3a.

Create the script “exercise3.R” and save it to the “Rcourse/Module1” directory: you will save all the commands of exercise 3 in that script.
Remember you can comment the code using #.

1- Go to Rcourse/Module1 First check where you currently are with getwd(); then go to Rcourse/Module1 with setwd()

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getwd()
setwd("Rcourse/Module1")
setwd("~/Rcourse/Module1")

2- Create vector w as:

w <- rep(x=c("miRNA", "mRNA"), times=c(3, 2))

3- View vector w in the console: how does function rep() work ?
Play with the times argument.

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rep(x=c("miRNA", "mRNA"), times=c(3, 4))

## [1] "miRNA" "miRNA" "miRNA" "mRNA"  "mRNA"  "mRNA"  "mRNA"

rep(x=c("miRNA", "mRNA"), times=c(10, 2))

##  [1] "miRNA" "miRNA" "miRNA" "miRNA" "miRNA" "miRNA" "miRNA" "miRNA"
##  [9] "miRNA" "miRNA" "mRNA"  "mRNA"

4- What is the output of table(w) ? What does the table function do ?

5- Type w[grep(pattern=“mRNA”, x=w)] and w[w == “mRNA”]
Is there a difference between the two outputs?

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w[grep(pattern="mRNA", w)]

## [1] "mRNA" "mRNA"

w[w == "mRNA"]

## [1] "mRNA" "mRNA"

# no difference between the outputs

6- Now type w[grep(pattern=“RNA”, w)] and w[w == “RNA”]
Is there a difference between the two outputs?

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w[grep(pattern="RNA", w)]

## [1] "miRNA" "miRNA" "miRNA" "mRNA"  "mRNA"

w[w == "RNA"]

## character(0)

# grep outputs 5 values but == outputs none

What is the difference between == and grep ?

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= looks for exact matches.
grep looks for patterns.

7- Create vector g as:

g <- c("hsa-let-7a", "hsa-mir-1", "CLC", "DKK1", "LPA")

How many elements do w and g contain?

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length(w); length(g)

## [1] 5

## [1] 5

8- Do vectors w and g have the same length? Use the function identical() to check this.

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identical(x=length(w), y=length(g))

## [1] TRUE

9- Name the elements of g using the elements of w.
(i.e. the names of each element of g will be the elements of w).

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names(g) <- w

If you have time, continue with Exercise 3b below.

9.3.2 Exercise 3b.

1- Use the sub() function to replace miRNA with microRNA in the names of g.

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names(g) <- sub(pattern="miRNA", replacement="microRNA", x=names(g))

2- Count how many microRNAs and mRNAs there are in g based on the column names.

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table(names(g))

## 
## microRNA     mRNA 
##        3        2

3- Create vector tt as:

tt <- "Introduction to R course"

How many characters does tt contain? Use nchar().

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nchar(tt)

## [1] 24

4- Remove “Introduction to R” from tt.
You can try with either substr() or gsub()

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substr(x=tt, start=17, stop=nchar(tt))

## [1] "R course"

gsub(pattern="Introduction to R", replacement="", x=tt)

## [1] " course"