prevalence_test: Prevalence test for a variable of a given feature

In JacobAgerbo/QuickFixR: Helps scientist with data explorative tasks with user interface

Prevalence test for a variable of a given feature

Description

Prevalence test for a variable of a given feature

Usage

prevalence_test(
  MAE,
  variable,
  tax_level,
  prev_threshold = 0.05,
  filtering_cutof = 0.001,
  datatype = c("logcpm", "relabu", "counts")
)

Arguments

MAE	A multi-assay experiment object
variable	Compare groups by binary variable e.g. 'Disease State'
tax_level	The classification level used for feature
prev_threshold	Threshold for prevalence testing. Defaults to 0.05
filtering_cutof	Cutoff for filtering prior the test. Defaults to 0.001
datatype	counts, relative abundance,logcpm

Value

A plotly object and a table of statistics

Examples

data_dir = system.file('inst/extdata/Disease_Challenge.rds', package = 'QuickFixR')
df <- readRDS(data_dir)
p <- prevalence_test(df,
                    tax_level='Genus',
                    variable='Disease_State',
                    datatype='relabu')
p

JacobAgerbo/QuickFixR documentation built on Sept. 20, 2023, 12:40 p.m.