Plot of DNA Sequence Alignement
This function plots an image of an alignment of nucleotide sequences.
## S3 method for class 'DNAbin' image(x, what, col, bg = "white", xlab = "", ylab = "", show.labels = TRUE, cex.lab = 1, legend = TRUE, grid = FALSE, show.bases = FALSE, base.cex = 1, base.font = 1, base.col = "black", ...)
x |
a matrix of DNA sequences (class |
what |
a vector of characters specifying the bases to visualize. If missing, this is set to “a”, “g”, “c”, “t”, “n”, and “-” (in this order). |
col |
a vector of colours. If missing, this is set to “red”,
“yellow”, “green”, “blue”, “grey”, and “black”. If it is
shorter (or longer) than |
bg |
the colour used for nucleotides whose base is not among
|
xlab |
the label for the x-axis; none by default. |
ylab |
Idem for the y-axis. Note that by default, the labels of the sequences are printed on the y-axis (see next option). |
show.labels |
a logical controlling whether the sequence labels
are printed ( |
cex.lab |
a single numeric controlling the size of the sequence labels.
Use |
legend |
a logical controlling whether the legend is plotted
( |
grid |
a logical controlling whether to draw a grid ( |
show.bases |
a logical controlling whether to show the base symbols
( |
base.cex, base.font, base.col |
control the aspect of the base
symbols (ignored if the previous is |
... |
further arguments passed to
|
The idea of this function is to allow flexible plotting and colouring of a nucleotide alignment. By default, the most common bases (a, g, c, t, and n) and alignment gap are plotted using a standard colour scheme.
It is possible to plot only one base specified as what
with a
chosen colour: this might be useful to check, for instance, the
distribution of alignment gaps (image(x, "-")
) or missing data
(see examples).
Emmanuel Paradis
data(woodmouse) image(woodmouse) rug(seg.sites(woodmouse), -0.02, 3, 1) image(woodmouse, "n", "blue") # show missing data image(woodmouse, c("g", "c"), "green") # G+C par(mfcol = c(2, 2)) ### barcoding style: for (x in c("a", "g", "c", "t")) image(woodmouse, x, "black", cex.lab = 0.5, cex.axis = 0.7) par(mfcol = c(1, 1)) ### zoom on a portion of the data: image(woodmouse[11:15, 1:50], c("a", "n"), c("blue", "grey")) grid(50, 5, col = "black") ### see the guanines on a black background: image(woodmouse, "g", "yellow", "black")
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