BWT Project

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rm(list=ls())

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First, run the following chunk to load the necessary libraries.


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```r
```r

library(stringr)
library(ottr)

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Second, run this chunk to make sure graphical output will work.


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```r
```r

options(bitmapType='cairo')

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```r
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library(readr)

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```r
```r
library(dplyr)

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```r
```r
arrange(seq)

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```r
```r
#comseq1<-list(\T\,\G\,\c\,\A\,\^\,\A\,\A\,\A\)
#comseq1

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```r
```r
#cat(paste(comseq1),sep =\\n\)

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```r
```r
comseq1 <- c('T', 'G', 'C', 'A', '^', 'A','A','A','A')
comseq1

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```r
```r
#cat(paste(x1),sep =\\n\)

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```r
```r
sort_comseq1<-sort(comseq1)
sort_comseq1

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#write the compressed sequence as a string. using a variable called compressed_seq1

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```r
```r
compressed_seq1<-(\TGCA^AAA\)
compressed_seq1

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#change the sequence from string to be as vector by using the function strsplit. using a variable called sequence_1

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```r
```r
sequence_2<-strsplit(compressed_seq1, \\)[[1]]
sequence_1<-strsplit(compressed_seq1, \\)[[1]]
sequence_1

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#use the function sort to make the sequence in an alphabetical order

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```r
```r
sort(sequence_1)

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```r
```r
cat(paste(sort(rep(sequence_1,)),sep =\\n\))

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```r
```r
for(i in 1:2) {                                   
  new <- rep(i, nrow(df))                       
  data[ , ncol(df) + 1] <- new                  
  colnames(df)[ncol(df)] <- paste0(\new\, i)  
}

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```r
```r
first_column<- c(\^\,\G\,\A\,\T\,\T\,\A\,\C\,\A\)
second_column<- sort(first_column)
third_column<-paste(first_column,second_column)

fourth_column<-sort(third_column)
#fifth_column<-paste(first_column,fourth_column)

#sixth_column<-sort(fifth_column)
#seventh_column<-paste(first_column,sixth_column)

#eight_column<-sort(seventh_column)
#ninth_coulmn<-paste(first_column,eight_column)

#tenth_coulmn<-sort(ninth_coulmn)
#elventh_coulmn<-paste(first_column,tenth_coulmn)

#twelveth_coulmn<-sort(elventh_coulmn)

#df<-data.frame(first_column,second_column,third_column,fourth_column,fifth_column,sixth_column,seventh_column,eight_column,ninth_coulmn,tenth_coulmn,elventh_coulmn,twelveth_coulmn)
df<-data.frame(first_column,second_column,third_column)
df

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```r
```r
first_column<- c(\^\,\G\,\A\,\T\,\T\,\A\,\C\,\A\)
second_column<- sort(first_column)
third_column<-paste(first_column,second_column)
fourth_column<-sort(third_column)
#df<-data.frame(first_column,second_column,third_column)
df<-data.frame(first_column, second_column, third_column, fourth_column)
df

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```r
```r
rm(list=ls())

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```r
```r

 first_column<- c(\^\,\G\,\A\,\T\,\T\,\A\,\C\,\A\)
for(i in first_column) { 
  column_variable<- cbind()
 
second_column<- sort(first_column)
third_column<-paste(first_column,second_column)
fourth_column<- sort(fourth_column)
length_1<-length(df)
  #new <- rep(i, nrow(df))                       
  #df[ , ncol(df) ] <- new                  
  #colnames(df)[ncol(df)] <- paste0(\new\, i) 
  #df<-cbind(df,sort(first_column))
}
df

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```r
```r
View(df)

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```r
```r
length_first_column<- length(first_column)
length_first_column

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```r
```r
str(df)

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```r
```r
df <- data.frame(x = c(6, 2), y = c(3, 6))

# Empty list
res <- vector(\list\, 2)

for(i in 1:ncol(df)) {
    for (j in 1:nrow(df)) {
        res[[j]][i] <- df[j, i] * 4
    }
}

res

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```r
```r
make <- function(x0, n) {
  f <- function(x, m) {
    if(m <= n) {
      y <- paste(x[[ncol(x)]], x0)
      y <- data.frame(y, sort(y))
      names(y) <- paste(\column\, m:(m + 1L), sep = \_\)
      out <- cbind(x, y)
      Recall(out, m + 2L)
    } else return(x)
  }
  x <- data.frame(x0, sort(x0))
  names(x) <- paste(\column\, 1:2, sep = \_\)
  f(x, 3L)
}

first_column<- c(\^\,\G\,\A\,\T\,\T\,\A\,\C\,\A\)
make(first_column, 8)

NA

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```r
x <- c(A=1, C=2, G=3, T=4, `^`= 5, `!`=6)
x

y <- "!^GATTACA"
s <- strsplit(y, "")[[1]]
i <- match(s, names(x))
i

s[c(3:length(s), 1, 2)]

[1] "G" "A" "T" "T" "A" "C" "A" "!" "^"

paste(s[c(3:length(s), 1, 2)], collapse = "")

[1] "GATTACA!^"

x = "!^GATTACA"
str_replace_all(x, c("A"="1", "C"="2", "G"="3", "T"="4", "\\^"="5", "\\!"="6"))

[1] "653144121"

You might like to try out knitting your document together as html now to see all the work you have done in the friendly html format.

Hopefully, this has given you some experience with the RStudio environment as well as objects, variables, data types and functions in the R language.

You should now have everything you need to tackle the next lesson, where we will learn how to import and manipulate data in R.

This is the end of the notebook.