Perform and plot a 3D Principal Components Analysis
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,
log_transform = FALSE,
log_transform_pseudocount = 0.5,
log_transform_base = "ln",
color_values = NULL,
plot_title = "PCA 3D",
plot_filename = "pca_3D.html",
print_plots = options::opt("print_plots"),
save_plots = options::opt("save_plots"),
plots_subdir = "pca",
...
)
## S7 method for class <MOSuite::multiOmicDataSet>
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,
log_transform = FALSE,
log_transform_pseudocount = 0.5,
log_transform_base = "ln",
color_values = NULL,
plot_title = "PCA 3D",
plot_filename = "pca_3D.html",
print_plots = options::opt("print_plots"),
save_plots = options::opt("save_plots"),
plots_subdir = "pca",
...
)
## S7 method for class <data.frame>
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,
log_transform = FALSE,
log_transform_pseudocount = 0.5,
log_transform_base = "ln",
color_values = NULL,
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
- count_type
the type of counts to use. Ignored when
moo_countsis already a dataframe.- sub_count_type
used if
count_typeis a list in the counts slot: specify the sub count type within the list.- sample_metadata
sample metadata as a data frame or tibble.
- feature_id_colname
The column from the counts data containing feature IDs. If
NULL, first column is used.- sample_id_colname
The column from sample metadata containing sample names. If
NULL, first column is used.- samples_to_rename
optional named mapping in
old_name: new_nameformat for display labels.- group_colname
The column from sample metadata containing sample group information.
- label_colname
The column from sample metadata containing sample labels.
- principal_components
vector with numbered principal components to plot
- point_size
size for
ggplot2::geom_point()- label_font_size
font size used for labels in the interactive figure.
- log_transform
If
TRUE, applylog(x + log_transform_pseudocount, base = log_transform_base)to sample count columns before PCA. Use this for count-like data such as raw, clean, filt, or CPM-like counts; leave itFALSEfor already normalized/log-scale or batch-corrected values to avoid double transformation.- log_transform_pseudocount
Pseudocount added before log-transforming counts when
log_transformisTRUE.- log_transform_base
Logarithm base to use when
log_transformisTRUE. Use a numeric value, or"e","ln", or"natural"for natural log. Default is"ln"to match the original PCA transform.- color_values
vector of colors as hex values or names recognized by R. Unnamed colors are assigned by factor level order when the grouping column is a factor; otherwise, they follow the order in which groups first appear in the metadata column. Defaults to
NULL; whenNULL,mosuite_paletteis used fordata.framedispatch and stored colors are used formultiOmicDataSetdispatch.- plot_title
title for the plot
- plot_filename
output filename when saving plots.
- print_plots
whether to print plot to the active graphics device.
- save_plots
whether to save plot to disk.
- plots_subdir
output subdirectory for saved plots.
- ...
additional arguments passed to methods
Value
plotly::plot_ly figure
See also
Other PCA functions:
calc_pca(),
plot_pca(),
plot_pca_2d()
