Introduction to dotplots in R

Sequence dotplots in R

By: Avril Coghlan.

Adapted, edited and expanded: Nathan Brouwer under the Creative Commons 3.0 Attribution License (CC BY 3.0).

NOTE: I’ve added some new material that is rather terse and lacks explication.

Good sources of more info: https://omicstutorials.com/interpreting-dot-plot-bioinformatics-with-an-example/

http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/650/Examples_interpretations_dot_plots.html

As a first step in comparing two protein, RNA or DNA sequences, it is a good idea to make a dotplot. A dotplot is a graphical method that allows the comparison of two protein or DNA sequences and identify regions of close similarity between them. A dotplot is essentially a two-dimensional matrix (like a grid), which has the sequences of the proteins being compared along the vertical and horizontal axes.

In order to make a simple dotplot to represent of the similarity between two sequences, individual cells in the matrix can be shaded black if residues are identical, so that matching sequence segments appear as runs of diagonal lines across the matrix. Identical proteins will have a line exactly on the main diagonal of the dotplot, that spans across the whole matrix.

For proteins that are not identical, but share regions of similarity, the dotplot will have shorter lines that may be on the main diagonal, or off the main diagonal of the matrix. In essence, a dotplot will reveal if there are any regions that are clearly very similar in two protein (or DNA) sequences.

Preliminaries

library(compbio4all)
library(rentrez)

Visualzing two identical sequences

To help build our intuition about dotplots we’ll first look at some artificial examples. First, we’ll see what happens when we make a dotplot comparing the alphabet versus itself. The build-in LETTERS object in R contains the alphabet from A to Z. This is a sequence with no repeats.

#LETTERS
seqinr::dotPlot(LETTERS,LETTERS)

What we get is a perfect diagonal line.

Visualizing repeats

We are created a larger dot plot that will be 54x54 as opposed to 27x27 above. There are more diagonal lines in the larger dot plot because there are multiple of the same “letters” being compared and are identical.

LETTERS.2.times  <- c(LETTERS, LETTERS)
length(LETTERS.2.times)

## [1] 52

seqinr::dotPlot(LETTERS.2.times,               LETTERS.2.times)

###In this code chunk we are just continuing to add more sequences to the dot plots to create larger plots. This dot plot is comparing the letters of the alphabet three times.

LETTERS.3.times <- c(LETTERS, LETTERS, LETTERS) 

seqinr::dotPlot (LETTERS.3.times, LETTERS.3.times) 

In this code chunk we are creating a dot plot that contains mulutiple repeats of the “LETTERS” function using the rep() function.

seq.repeat <- c("A","C","D","E","F","G","H","I")

# rep (), 2 arguments: vector, and number of repeates
seq1 <- rep(seq.repeat, 3)

Make the dotplot:

seqinr::dotPlot(seq1, seq1)

Inversions and Dot Plots

###We are inverting the sequence of letters in order to be able to comapre the forward and inverted sequences of letters. This will create a different pattern in a dot plot that we have not seen before.

“invert” means “inversion”

LETTERS.3.times.with.invert <- c(LETTERS, rev(LETTERS), LETTERS) 

seqinr::dotPlot( LETTERS.3.times.with.invert, LETTERS.3.times.with.invert )

###This code chunk functions to take the letters and segment them into three sections that we can look at and compare in a dot plot. The code chunk also incudes a translocation.

seg1 <- LETTERS[1:8]
seg2 <-  LETTERS[9:18]
seg3 <-  LETTERS[19:26]

#translocation
LETTERS.with.transloc <- c(seg1, seg2, seg3) 
seqinr::dotPlot(LETTERS.with.transloc, LETTERS.with.transloc) 

SAMPLING

This code chunk is where we are sampling our data. The first code chunk below is sampling with replacement, designated by replace = T (true). The output is 26 random letters chosen by the function with replacement of the letters once they are chosen.

sample(x = LETTERS, size = 26, replace = T)

##  [1] "H" "E" "E" "Z" "U" "S" "E" "Y" "G" "N" "U" "H" "J" "T" "O" "J" "I" "P" "B"
## [20] "N" "M" "U" "R" "P" "A" "W"

###The code chunk below shows us taking random samples of letters and creating dot plots with the random letters.

letters.rand1 <- sample(x = LETTERS, size = 26, replace = F)
letters.rand2 <- sample(x= LETTERS, size = 26, replace = F)


seqinr::dotPlot(letters.rand1, letters.rand1)

Download sequences

Now we’ll make a real dotplot of the chorismate lyase proteins from two closely related species, Mycobacterium leprae and Mycobacterium ulcerans.

Note - these are protein sequences so db = “protein”

In this code chunk we are calling up the fasta file for chorismate lyase and two closely related species, adding them to new “objects” in R Studio, and then

# sequence 1: Q9CD83
leprae_fasta <- rentrez::entrez_fetch(db = "protein",
                        id = "Q9CD83",
                         rettype = "fasta")
# sequence 2: OIN17619.1
ulcerans_fasta <- rentrez::entrez_fetch(db ="protein",
                         id = "OIN17619.1",
                         rettype = "fasta")


leprae_vector   <- compbio4all::fasta_cleaner(leprae_fasta) 
ulcerans_vector <- compbio4all:: fasta_cleaner(ulcerans_fasta) 

Comparing Sequences with DotPlots

We can create a dotplot for two sequences using the dotPlot() function in the seqinr package.

First, let’s look at a dotplot created using only a single sequence. This is frequently done to investigate a sequence for the presence of repeats.

(Note - and older version of this exercise stated this kind of anlysis wasn’t normally done; this was written last year before I knew of the use of dotplots for investigating sequence repeats.)

seqinr::dotPlot(leprae_vector, ulcerans_vector)

##The sequences show a strong line across the diagonal of the dot plot. This shows that the sequences are very similar to one another.

In the dotplot above, the M. leprae sequence is plotted along the x-axis (horizontal axis), and the M. ulcerans sequence is plotted along the y-axis (vertical axis). The dotplot displays a dot at points where there is an identical amino acid in the two sequences.

For example, if amino acid 53 in the M. leprae sequence is the same amino acid (eg. “W”) as amino acid 70 in the M. ulcerans sequence, then the dotplot will show a dot the position in the plot where x =50 and y =53.

In this case you can see a lot of dots along a diagonal line, which indicates that the two protein sequences contain many identical amino acids at the same (or very similar) positions along their lengths. This is what you would expect, because we know that these two proteins are homologs (related proteins) because they share a close evolutionary history.