2.RPrep

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Objective: Get a basic working knowledge of R

Time estimated: 2 h; taken * h;

Date started: 2023-1-15 ; completed: 2023-1-12

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Getting help

• Using ?? or apropos("^med") *# ^/$ all functions that begin/end with the string*

Basics of R syntax

• Predict

  7 %% 2# Modulo operation (remainder of integer division)7 %/% 2# Integer division
  
  TRUE&FALSE # Returns FALSE
  TRUE|FALSE # TRUE
  
  >!(FALSE | (! FALSE))
  FALSE

• Task: Practice

  (lastNum<6 | lastNum > 10)
  (lastNum >= 10 & lastNum <20)
  (2 == (((lastNum/7- (((10*lastNum/7)%/%1)/10)) /100)%/%1)^(1/3))

R scalars and vectors

summary(myVec)[c("Max", "Min")] == summary(myVec)[c(2, 5)] # 2nd and 5th
summary(myVec)["Median"] == summary(myVec)[3]

Matrices and higher-dimensional objects

• Use matrix()or array()put togerther with rbind() or cbind() (row or column)

• dim() for new mattrix

  > dim(a) <- c(2,6)
  > a 
  			[,1] [,2] [,3] [,4] [,5] [,6]
  [1,]    1    3    5    7    9   11
  [2,]    2    4    6    8   10   12
  
  m[3:4, 1:2] # submatrix: rows 3 to 4 and columns 1 to 2

Data frames & Subsetting

• Recall from MGY441, grepl is logical

LPSdat[grepl("Il", LPSdat$genes) & grepl("ra", LPSdat$genes), 1:2]

Lists

( plasmidData <- read.table(
                    file.path("data_files","plasmidData.tsv"),
                    sep="\t",
                    header=TRUE,
                    stringsAsFactors = FALSE) )
# column 1 as rownames
rownames(plasmidData) <- plasmidData[ , 1]

• Change row name

row.names(plasmidData)[4] <- “pMAL-p5x”

• get all elements

lapply(plasmidDB, function(x) { return(x$ori) })

Control structures

• Task: Practice

  count <- 0
  add <- 3
  res <- c()
  while(count<=3){
      res[count+1] <- (add - count)
      count <- count + 1
  }
  res[count+1] <- "Lift Off!"
  res
  
  txt <- c(txt, "Lift Off!") #alternative solution

💡 **Conclusion and outlook**: Finished R recap