Conditional branching and looping in R

These exercises are about the conditions and loops sections of Introduction to R.

Exercise 1 - If Else

Build an if statement that test if x is a negative number. Write a print statement that will confirm if x is less than 0. Test it with several values of x.

x<- 42

if (x<0){
  print("It's a negative number!")
}

x <- -42

if (x<0){
  print("It's a negative number!")
}

## [1] "It's a negative number!"

Modify the previous if statement to include an else. Ensure a print statement is returned to say if the number is not negative.

x <- 0

if (x<0){
  print("It's a negative number!")
}else{
  print("It's not a negative number!")
}

## [1] "It's not a negative number!"

x <- -1

if (x<0){
  print("It's a negative number!")
}else{
  print("It's not a negative number!")
}

## [1] "It's a negative number!"

Finally add a else if statement. We want a response to confirm if x is negative, positive or if it is zero.

x <- -1

if (x<0){
  print("It's a negative number!")
}else if (x==0){
  print("It's zero")
}else{
  print("It's a positive number!")
}

## [1] "It's a negative number!"

x <- 0

if (x<0){
  print("It's a negative number!")
}else if (x==0){
  print("It's zero")
}else{
  print("It's a positive number!")
}

## [1] "It's zero"

x <- 1

if (x<0){
  print("It's a negative number!")
}else if (x==0){
  print("It's zero")
}else{
  print("It's a positive number!")
}

## [1] "It's a positive number!"

Build an if/else statement that test if a variable is odd/even. Include x in the printed output.

Hint: The modulus operator may be useful here i.e. x%%2 returns the remainder after the value of x is divided by 2.

x <- 1

if (x%%2==0){
  paste(x,"is even")
}else{
  paste(x,"is odd")
}

## [1] "1 is odd"

x <- 2

if (x%%2==0){
  paste(x,"is even")
}else{
  paste(x,"is odd")
}

## [1] "2 is even"

– Using an ifelse() expression, create a factor from a vector of 1 to 40 where all numbers less than 10 are “small”,10 to 30 are “mid”,31 to 40 are “big”

condExercise <- 1:40
condExercise

##  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
## [26] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

vectorResult <- ifelse(condExercise<10,"small",ifelse(condExercise < 31,"mid","big"))
temp <- factor(vectorResult,levels=c("small","mid","big"),order=T)
temp

##  [1] small small small small small small small small small mid   mid   mid  
## [13] mid   mid   mid   mid   mid   mid   mid   mid   mid   mid   mid   mid  
## [25] mid   mid   mid   mid   mid   mid   big   big   big   big   big   big  
## [37] big   big   big   big  
## Levels: small < mid < big

– Calculate the factorial (factorial of 3 = 3 * 2 * 1) of 10 using a loop.

for(x in 1:10){
  if(x == 1){
    factorialAnswer <- 1
  }else{
    factorialAnswer <- factorialAnswer * x 
  }
}
factorialAnswer

## [1] 3628800

– Adjusting your answer from before, what is the first number that has a factorial greater than 1000.

factorialAnswer <- 0
count <- 0

while(factorialAnswer <= 1000){
  count <- count+1
  if(count == 1){
    factorialAnswer <- 1
  }else{
    factorialAnswer <- factorialAnswer * count 
  }
}
count

## [1] 7

Set your working directory to be in the downloaded course material. Specifically the r_course subdirectory. [The exact path will depend on where you have save your download]. Read in all files from expression directory (“ExpressionResults/”) with .txt extension and create a table of gene expression results.

setwd("~/Downloads/Intro_To_R_1Day-master/r_course")

filesToRead <- dir("ExpressionResults/",pattern = "*\\.txt",full.names=T)
fileRead <- vector("list",length=length(filesToRead))

for(i in 1:length(filesToRead)){
  fileRead[[i]] <- read.delim(filesToRead[i],header=F,sep="\t")
  colnames(fileRead[[i]]) <- c("GeneNames",basename(filesToRead[i]))
}
mergedTable <- NULL
for(i in fileRead){
  if(is.null(mergedTable)){
    mergedTable <- i
  }else{
    mergedTable <- merge(mergedTable,i,by=1,all=T)
  }
  
  print(nrow(mergedTable))
}

## [1] 5001
## [1] 5001
## [1] 5001
## [1] 5001
## [1] 5001
## [1] 5001
## [1] 5001
## [1] 5001
## [1] 5001
## [1] 5001
## [1] 5001

mergedTable[1:3,]

##   GeneNames Annotation.txt        <NA> ExpressionResults_Sample1.txt
## 1    Gene_1       Ens_1001 DNA_Binding                      3.448466
## 2   Gene_10      Ens_10010 DNA_Binding                      5.314180
## 3  Gene_100     Ens_100100 DNA_Binding                      5.591612
##   ExpressionResults_Sample10.txt ExpressionResults_Sample2.txt
## 1                       7.665488                      5.250063
## 2                       7.813501                      5.361170
## 3                       5.186500                      6.840497
##   ExpressionResults_Sample3.txt ExpressionResults_Sample4.txt
## 1                      5.968927                      6.868251
## 2                      5.305980                      6.742855
## 3                      5.197710                      5.922931
##   ExpressionResults_Sample5.txt ExpressionResults_Sample6.txt
## 1                      5.367100                      5.189686
## 2                      5.957786                      6.293098
## 3                      6.813154                      6.228178
##   ExpressionResults_Sample7.txt ExpressionResults_Sample8.txt
## 1                      3.882930                      5.329258
## 2                      7.361497                      6.649428
## 3                      5.831575                      6.653152
##   ExpressionResults_Sample9.txt
## 1                      6.167451
## 2                      6.213910
## 3                      3.992555

– Add annotation from Annotation.txt. How do the pathway information for genes compare between expression table and annotation table.

Annotation <- read.table("ExpressionResults/Annotation.txt",sep="\t",h=T)
annotatedExpression <- merge(Annotation,mergedTable,by=1,all.x=F,all.y=T)
annotatedExpression[1:2,]

##   GeneName   Ensembl     Pathway Annotation.txt        <NA>
## 1   Gene_1  Ens_1001 DNA_Binding       Ens_1001 DNA_Binding
## 2  Gene_10 Ens_10010 DNA_Binding      Ens_10010 DNA_Binding
##   ExpressionResults_Sample1.txt ExpressionResults_Sample10.txt
## 1                      3.448466                       7.665488
## 2                      5.314180                       7.813501
##   ExpressionResults_Sample2.txt ExpressionResults_Sample3.txt
## 1                      5.250063                      5.968927
## 2                      5.361170                      5.305980
##   ExpressionResults_Sample4.txt ExpressionResults_Sample5.txt
## 1                      6.868251                      5.367100
## 2                      6.742855                      5.957786
##   ExpressionResults_Sample6.txt ExpressionResults_Sample7.txt
## 1                      5.189686                      3.882930
## 2                      6.293098                      7.361497
##   ExpressionResults_Sample8.txt ExpressionResults_Sample9.txt
## 1                      5.329258                      6.167451
## 2                      6.649428                      6.213910

summary(annotatedExpression$Pathway)

##    Length     Class      Mode 
##      5001 character character

summary(Annotation$Pathway)

##    Length     Class      Mode 
##      5000 character character

Conditional branching and looping in R

Rockefeller University, Bioinformatics Resource Centre

https://rockefelleruniversity.github.io/Intro_To_R_1Day/