#' Data visualization by pie chart / box plot
#'
#' @param MAE A multi-assay experiment object
#' @param samples_discard The list of samples to filter
#' @param filter_type Either 'By Microbes' or 'By Metadata'
#' @param sample_condition Which condition to check e.g. 'SEX'
#' @return A plotly object
#'
#' @examples
#' data_dir <- system.file("extdata/MAE.rds", package = "animalcules")
#' toy_data <- readRDS(data_dir)
#' result <- filter_summary_pie_box(toy_data,
#' samples_discard = c("subject_2", "subject_4"),
#' filter_type = "By Microbes",
#' sample_condition = "SEX"
#' )
#' result
#'
#' @import dplyr
#' @import plotly
#' @import magrittr
#' @import reshape2
#' @import MultiAssayExperiment
#'
#' @export
filter_summary_pie_box <- function(MAE,
samples_discard = NULL,
filter_type,
sample_condition) {
# Subset the data
MAE_subset <-
mae_pick_samples(MAE = MAE, discard_samples = samples_discard)
# Extract data
microbe <- MAE_subset[["MicrobeGenetics"]]
# host <- MAE_subset[['HostGenetics']]
sam_table <- as.data.frame(colData(microbe)) # sample x condition
counts_table <-
as.data.frame(assays(microbe))[, rownames(sam_table)] #organism x sample
# Add count summary data to sample table
sam_table[, "Reads"] <- colSums(counts_table[, rownames(sam_table)])
sam_table[, "Taxnum"] <- apply(counts_table, 2, function(x) sum(x >= 1))
# select filter type
if (filter_type == "Microbes") {
cov <- "Taxnum"
} else {
cov <- sample_condition
}
# Use density plot if the variable has more than
# 8 unique values Use pie chart if
# the variable has less than 8 unique values
num_levels <- length(unique(unlist(sam_table[, cov])))
if (num_levels > 8 & num_levels / nrow(sam_table) >=
0.3 & !is.character(unlist(sam_table[
,
cov
]))) {
vec <- unlist(sam_table[, cov])
hover.txt <- paste(rownames(sam_table), ", ", vec, sep = "")
num.scatter <- plotly::plot_ly(
y = vec, jitter = 0.3,
pointpos = -1.8, boxpoints = "all",
hoverinfo = "text",
text = hover.txt,
marker = list(color = "rgb(7,40,89)"),
line = list(color = "rgb(7,40,89)"),
name = cov, type = "box"
) %>%
layout(title = cov, yaxis = list(title = cov))
num.scatter$elementId <- NULL
return(num.scatter)
} else {
cat.df <- data.frame(table(sam_table[, cov]))
cat.pie <- plotly::plot_ly(cat.df,
labels = ~Var1,
values = ~Freq, type = "pie",
showlegend = FALSE
) %>% layout(title = cov)
cat.pie$elementId <- NULL
return(cat.pie)
}
}
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