update

lot of changes!!!

R/bars_fun.R

@@ -31,6 +31,32 @@ rarefaction <- function(data = data, col = NULL, step = 100, ggplotly = TRUE){
 }
 
 
+#' aggregate_top_taxa from microbiome package
+#'
+#'
+#' @param x phyloseq object
+#' @param top Keep the top-n taxa, and merge the rest under the category 'Other'. Instead of top-n numeric this can also be a character vector listing the groups to combine.
+#' @param level Summarization level (from ‘rank_names(pseq)’)
+#'
+#' @importFrom microbiome aggregate_taxa
+#' @importFrom microbiome top_taxa
+#'
+#' @export
+
+aggregate_top_taxa <- function (x, top, level){
+    x <- aggregate_taxa(x, level)
+    tops <- top_taxa(x, top)
+    tax <- tax_table(x)
+    inds <- which(!rownames(tax) %in% tops)
+    tax[inds, level] <- "Other"
+    tax_table(x) <- tax
+    tt <- tax_table(x)[, level]
+    tax_table(x) <- tax_table(tt)
+    aggregate_taxa(x, level)
+}
+
+
+
 #' Barplots plotly
 #'
 #'
@@ -48,7 +74,6 @@ rarefaction <- function(data = data, col = NULL, step = 100, ggplotly = TRUE){
 #' @return Returns barplots in an interactive plotly community plot
 #'
 #' @import plotly
-#' @importFrom microbiome aggregate_top_taxa
 #' @importFrom reshape2 melt
 #' @importFrom gtools mixedsort
 #' @importFrom dplyr group_map group_by across
@@ -75,6 +100,8 @@ if( all(Ord1 != sample_variables(data)) | all(Fact1 != sample_variables(data))){
   Fdata = data
   psobj.top <- aggregate_top_taxa(Fdata, rank, top = top)
 
+
+
   # print("get data")
   sdata <- as.data.frame(sample_data(psobj.top), stringsAsFactors = TRUE)
   # sdata$sample.id = sample_names(psobj.top)