Skip to content

3D PCA for counts dataframe

Source: R/plot_pca.R
plot_pca_3d.Rd

3D PCA for counts dataframe

Usage

plot_pca_3d(
  counts_dat,
  sample_metadata,
  sample_id_colname = NULL,
  samples_to_rename = NULL,
  group_colname = "Group",
  label_colname = "Label",
  principal_components = c(1, 2, 3),
  point_size = 8,
  label_font_size = 24,
  color_values = c("#5954d6", "#e1562c", "#b80058", "#00c6f8", "#d163e6", "#00a76c",
    "#ff9287", "#008cf9", "#006e00", "#796880", "#FFA500", "#878500"),
  plot_title = "PCA 3D"
)

Arguments

counts_dat

data frame of feature counts (e.g. expected feature counts from RSEM).

sample_metadata

sample metadata as a data frame or tibble.

sample_id_colname

The column from the sample metadata containing the sample names. The names in this column must exactly match the names used as the sample column names of your input Counts Matrix. (Default: NULL - first column in the sample metadata will be used.)

samples_to_rename

If you do not have a Plot Labels Column in your sample metadata table, you can use this parameter to rename samples manually for display on the PCA plot. Use "Add item" to add each additional sample for renaming. Use the following format to describe which old name (in your sample metadata table) you want to rename to which new name: old_name: new_name

group_colname

The column from the sample metadata containing the sample group information. This is usually a column showing to which experimental treatments each sample belongs (e.g. WildType, Knockout, Tumor, Normal, Before, After, etc.).

label_colname

The column from the sample metadata containing the sample labels as you wish them to appear in the plots produced by this template. This can be the same Sample Names Column. However, you may desire different labels to display on your figure (e.g. shorter labels are sometimes preferred on plots). In that case, select the column with your preferred Labels here. The selected column should contain unique names for each sample. (Default: NULL – sample_id_colname will be used.)

principal_components

vector with numbered principal components to plot (Default: c(1,2,3))

point_size

size for ggplot2::geom_point()

label_font_size

label font size for the PCA plot

color_values

vector of colors as hex values or names recognized by R

plot_title

title for the plot

Value

plotly::plot_ly figure

See also

plot_pca generic

Other PCA functions: calc_pca(), plot_pca(), plot_pca_2d()