| plot.lddf | R Documentation |
mldest() or
sldest() using corrplot()Formats the LD estimates in the form of a matrix and creates a heatmap of
these estimates. This heatmap is created using the
corrplot R package. I've adjusted a lot of the defaults
to suit my visualization preferences.
## S3 method for class 'lddf'
plot(
x,
element = "r2",
type = c("upper", "full", "lower"),
method = c("color", "circle", "square", "ellipse", "number", "shade", "pie"),
diag = FALSE,
is.corr = NULL,
tl.pos = "n",
title = NULL,
na.label = "square",
...
)
x |
An object of class |
element |
Which element of |
type |
Character, |
method |
See |
diag |
Logical, whether display the correlation coefficients on the principal diagonal. |
is.corr |
See |
tl.pos |
See |
title |
What should the title be? Defaults to the element name. |
na.label |
See |
... |
Additional arguments to pass to
|
For greater plotting flexibility, see corrplot()
for the parameter options.
(Invisibly) returns a matrix of the selected elements.
David Gerard
set.seed(1)
## Simulate genotypes when true correlation is 0
nloci <- 5
nind <- 100
K <- 6
nc <- 1
genomat <- matrix(sample(0:K, nind * nloci, TRUE), nrow = nloci)
## Haplotypic LD estimates
lddf <- mldest(geno = genomat,
K = K,
nc = nc,
type = "hap")
## Plot estimates of z
plot(lddf, element = "z")
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