filter_categorize: Categorize continuous variables

In animalcules: Interactive microbiome analysis toolkit

Description

Categorize continuous variables

Usage

filter_categorize(
  sam_table,
  sample_condition,
  new_label,
  nbins = NULL,
  bin_breaks = c(),
  bin_labels = c()
)

Arguments

sam_table	A sample x condition dataframe
sample_condition	Continuous variable to categorize
new_label	Column name for categorized variable
nbins	Auto select ranges for n bins/categories
bin_breaks	Manually select ranges for bins/categories
bin_labels	Manually label bins/categories

Value

A list with an updated sample table and before/after plots

Examples

library(SummarizedExperiment)
data_dir = system.file('extdata/MAE.rds', package = 'animalcules')
toy_data <- readRDS(data_dir)
microbe <- MultiAssayExperiment::experiments(toy_data)[[1]]
samples <- as.data.frame(colData(microbe))
result <- filter_categorize(samples,
                            sample_condition = 'AGE',
                            new_label='AGE_GROUP',
                            bin_breaks=c(0,55,75,100),
                            bin_labels=c('Young','Adult','Elderly'))
result$sam_table
result$plot.unbinned
result$plot.binned

animalcules documentation built on Nov. 8, 2020, 6:47 p.m.