#' Create barplot of average cell type composition
#'
#' @param prop_long data.frame of cell type portions in long form
#' @param sample_col name of column that identifies samples
#' @param x_col category to divide samples by
#' @param prop_col name of column containing proportion values
#' @param ct_col name of column containing cell type names
#' @param add_text Add rounded proportion value to bars
#' @param min_prop_text Minimum proportion to display text
#'
#' @return stacked barplot representing mean proportion of cell types for each group
#' @export
#'
#' @examples
#' pd <- SummarizedExperiment::colData(rse_bulk_test) |>
#' as.data.frame()
#'
#' est_prop_long <- est_prop |>
#' tibble::rownames_to_column("RNum") |>
#' tidyr::pivot_longer(!RNum, names_to = "cell_type", values_to = "prop") |>
#' dplyr::inner_join(pd |> dplyr::select(RNum, Dx)) ## TODO fix example data
#'
#' plot_composition_bar(est_prop_long)
#' plot_composition_bar(est_prop_long, x_col = "Dx")
#' plot_composition_bar(est_prop_long, x_col = "Dx", min_prop_text = 0.1)
#' plot_composition_bar(est_prop_long, x_col = "RNum", add_text = FALSE) + ggplot2::facet_wrap(~Dx, scales="free_x")
#'
#' @importFrom dplyr rename group_by summarise mutate arrange
#' @importFrom ggplot2 ggplot geom_bar geom_text aes theme element_text
plot_composition_bar <- function(
prop_long,
sample_col = "RNum",
x_col = "ALL",
prop_col = "prop",
ct_col = "cell_type",
add_text = TRUE,
min_prop_text = 0) {
x_cat <- cell_type <- anno_y <- NULL
# ct_col <- dplyr::enquo(ct_col)
mean_prop <- .get_cat_prop(prop_long, sample_col, x_col, prop_col, ct_col) |>
dplyr::ungroup()
if (x_col == "ALL") x_col <- NULL
comp_barplot <- ggplot2::ggplot(
data = mean_prop,
ggplot2::aes(x = x_cat, y = mean_prop, fill = cell_type)
) +
ggplot2::geom_bar(stat = "identity") +
ggplot2::labs(x = x_col, y = "Mean Proportion", fill = "Cell Type") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust = 1))
if (add_text) {
comp_barplot <- comp_barplot +
ggplot2::geom_text(ggplot2::aes(
y = mean_prop,
label = ifelse(mean_prop > min_prop_text,
format(round(mean_prop, 3), 3),
"")
),
position = ggplot2::position_stack(vjust = 0.5))
}
return(comp_barplot)
}
.get_cat_prop <- function(
prop_long,
sample_col = "RNum",
x_col = "ALL",
prop_col = "prop",
ct_col = "cell_type") {
cell_type <- prop <- mean_prop <- x_cat <- anno_y <- sum_prop <- n <- NULL
prop_long <- prop_long |>
dplyr::mutate(ALL = "ALL",
sample = !!as.symbol(sample_col)) |>
dplyr::rename(cell_type = ct_col, prop = prop_col, x_cat = x_col)
n_sample <- prop_long |>
dplyr::group_by(x_cat) |>
dplyr::summarise(n = length(unique(sample)))
cat_prop <- prop_long |>
dplyr::group_by(cell_type, x_cat) |>
dplyr::mutate(sum_prop = sum(prop)) |>
dplyr::slice(1) |>
dplyr::left_join(n_sample, by = "x_cat") |>
dplyr::mutate(mean_prop = sum_prop / n) |>
dplyr::arrange(cell_type) |>
dplyr::group_by(x_cat)
return(cat_prop)
}
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