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Add Option to Plot Percentage of Variance Explained in ElbowPlot Func… #8929

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Add Option to Plot Percentage of Variance Explained in ElbowPlot Func… #8929

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31 changes: 24 additions & 7 deletions R/visualization.R
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Original file line number Diff line number Diff line change
Expand Up @@ -4631,8 +4631,9 @@ DotPlot <- function(
#' Jackstraw
#'
#' @param object Seurat object
#' @param ndims Number of dimensions to plot standard deviation for
#' @param reduction Reduction technique to plot standard deviation for
#' @param ndims Number of dimensions to plot
#' @param reduction Reduction technique to plot (default is 'pca')
#' @param plot_type Type of plot to generate. Options are 'stdev' or 'variance'
#'
#' @return A ggplot object
#'
Expand All @@ -4645,7 +4646,10 @@ DotPlot <- function(
#' data("pbmc_small")
#' ElbowPlot(object = pbmc_small)
#'
ElbowPlot <- function(object, ndims = 20, reduction = 'pca') {
ElbowPlot <- function(object, ndims = 20, reduction = 'pca', plot_type = c("stdev", "variance")) {
# Ensure plot_type is either "stdev" or "variance"
plot_type <- match.arg(plot_type)

data.use <- Stdev(object = object, reduction = reduction)
if (length(x = data.use) == 0) {
stop(paste("No standard deviation info stored for", reduction))
Expand All @@ -4654,21 +4658,34 @@ ElbowPlot <- function(object, ndims = 20, reduction = 'pca') {
warning("The object only has information for ", length(x = data.use), " reductions")
ndims <- length(x = data.use)
}
stdev <- 'Standard Deviation'
plot <- ggplot(data = data.frame(dims = 1:ndims, stdev = data.use[1:ndims])) +
geom_point(mapping = aes_string(x = 'dims', y = 'stdev')) +

if (plot_type == "variance") {
# Calculate variance explained
variance_explained <- data.use^2 / sum(data.use^2) * 100
y_label <- "Percentage of Variance Explained"
y_data <- variance_explained[1:ndims]
} else {
# Standard deviation
y_label <- "Standard Deviation"
y_data <- data.use[1:ndims]
}

plot <- ggplot(data = data.frame(dims = 1:ndims, y_data = y_data)) +
geom_point(mapping = aes_string(x = 'dims', y = 'y_data')) +
labs(
x = gsub(
pattern = '_$',
replacement = '',
x = Key(object = object[[reduction]])
),
y = stdev
y = y_label
) +
theme_cowplot()

return(plot)
}


#' Boxplot of correlation of a variable (e.g. number of UMIs) with expression
#' data
#'
Expand Down