This function conducts Sparse Partial Least Squares Discriminant Analysis
(sPLS-DA) on the provided data. It uses the specified group_col (and
optionally group_col2) to define class labels while assuming the remaining
columns contain continuous variables. The function supports a log2
transformation via the scale parameter and generates a series of plots,
including classification plots, scree plots, loadings plots, and VIP score
plots. Optionally, ROC curves are produced when roc is TRUE.
Additionally, cross-validation is supported via LOOCV or Mfold methods. When
both group_col and group_col2 are provided and differ, the function
analyzes each treatment level separately.
cyt_splsda(
data,
group_col = NULL,
group_col2 = NULL,
colors = NULL,
pdf_title,
ellipse = FALSE,
bg = FALSE,
conf_mat = FALSE,
var_num,
cv_opt = NULL,
fold_num = 5,
scale = NULL,
comp_num = 2,
pch_values,
style = NULL,
roc = FALSE,
verbose = FALSE,
seed = 123
)Plots consisting of the classification figures, component figures with Variable of Importance in Projection (VIP) scores, and classifications based on VIP scores greater than 1. ROC curves and confusion matrices are also produced if requested.
A matrix or data frame containing the variables. Columns not
specified by group_col or group_col2 are assumed to be continuous
variables for analysis.
A string specifying the column name that contains the first group
information. If group_col2 is not provided, an overall analysis will
be performed.
A string specifying the second grouping column. Default is
NULL.
A vector of colors for the groups or treatments. If
NULL, a random palette (using rainbow) is generated based on
the number of groups.
A string specifying the file name for saving the PDF output.
Default is NULL which generates figures in the current graphics device.
Logical. Whether to draw a 95\
figures. Default is FALSE.
Logical. Whether to draw the prediction background in the figures.
Default is FALSE.
Logical. Whether to print the confusion matrix for the
classifications. Default is FALSE.
Numeric. The number of variables to be used in the PLS-DA model.
Character. Option for cross-validation method: either
"loocv" or "Mfold". Default is NULL.
Numeric. The number of folds to use if cv_opt is
"Mfold". Default is 5.
Character. Option for data transformation; if set to
"log2", a log2 transformation is applied to the continuous
variables. Default is NULL.
Numeric. The number of components to calculate in the sPLS-DA model. Default is 2.
A vector of integers specifying the plotting characters (pch values) to be used in the plots.
Character. If set to "3D" or "3d" and
comp_num equals 3, a 3D plot is generated using the
plot3D package. Default is NULL.
Logical. Whether to compute and plot the ROC curve for the model.
Default is FALSE.
A logical value indicating whether to print additional
informational output to the console. When TRUE, the function will
display progress messages, and intermediate results when
FALSE (the default), it runs quietly.
An integer specifying the seed for reproducibility (default is 123).
When verbose is set to TRUE, additional diagnostic plots (e.g., VIP plots, ROC Plots, Cross-Validation Plots)
are printed to the console. These plots provide extra insight into the model's performance
but can be suppressed by keeping verbose = FALSE.
# Loading Sample Data
data_df <- ExampleData1[,-c(3)]
data_df <- dplyr::filter(data_df, Group != "ND", Treatment != "Unstimulated")
cyt_splsda(data_df, pdf_title = NULL,
colors = c("black", "purple"), bg = FALSE, scale = "log2",
conf_mat = FALSE, var_num = 25, cv_opt = NULL, comp_num = 2,
pch_values = c(16, 4), style = NULL, ellipse = TRUE,
group_col = "Group", group_col2 = "Treatment", roc = FALSE, verbose = FALSE)
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