3D PCA for counts dataframe

Usage

plot_pca_3d(
  moo_counts,
  count_type = NULL,
  sub_count_type = NULL,
  sample_metadata = NULL,
  feature_id_colname = NULL,
  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",
  plot_filename = "pca_3D.html",
  print_plots = options::opt("print_plots"),
  save_plots = options::opt("save_plots"),
  plots_subdir = "pca"
)

Arguments

moo_counts: counts dataframe or multiOmicDataSet containing count_type & sub_count_type in the counts slot
count_type: the type of counts to use – must be a name in the counts slot (moo@counts)
sub_count_type: used if count_type is a list in the counts slot: specify the sub count type within the list. Must be a name in names(moo@counts[[count_type]]).
sample_metadata: sample metadata as a data frame or tibble.
feature_id_colname: The column from the counts dataa containing the Feature IDs (Usually Gene or Protein ID). This is usually the first column of your input Counts Matrix. Only columns of Text type from your input Counts Matrix will be available to select for this parameter. (Default: NULL - first column in the counts matrix will be used.)
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
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
plot_filename: plot output filename - only used if save_plots is TRUE
print_plots: Whether to print plots during analysis (Defaults to FALSE, overwritable using option 'moo_print_plots' or environment variable 'MOO_PRINT_PLOTS')
save_plots: Whether to save plots to files during analysis (Defaults to TRUE, overwritable using option 'moo_save_plots' or environment variable 'MOO_SAVE_PLOTS')
plots_subdir: subdirectory in figures/ where plots will be saved if save_plots is TRUE

Value

plotly::plot_ly figure

3D PCA for counts dataframe

Usage

Arguments

Value

See also