Description Usage Arguments Details Examples
Plots either the first 2 or 3 principal components, with the data points labelled accordng to chosen meta data in the mip data set.
1 | plot_pca(pca, num_components = 2, meta_var = "Country")
|
pca |
output of |
num_components |
numeric for number of components used. Default = 2 |
meta_var |
character for the desired meta variable to be used for labelling the scatterplot. Default = "Country". |
Using the output of pca_mip_data
and a specified variable
within the mip data set, e.g the country of sample collection, a
scatterplot of the data is produced. Either the first 2 or 3 components
can be used, as specified with 'num_components'. The chosen 'meta_var'
must be a variable found within the mip data set (this is included as
the last element in the object returned by pca_mip_data
).
1 2 3 4 5 6 7 8 | dat <- dummy_data()
dat <- filter_misc(dat = dat)
dat <- filter_coverage(dat = dat, min_coverage = 2)
dat <- melt_mip_data(dat = dat)
dat <- impute_mip_data(dat = dat)
pca <- pca_mip_data(dat = dat)
plot_pca(pca, num_components = 2, meta_var = "Country")
plot_pca(pca, num_components = 3, meta_var = "Study")
|
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