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Wrapper for One-way Anova statistical test

Usage

wrapperClassic1wayAnova(obj, i, with_post_hoc = "No", post_hoc_test = "No")

Arguments

obj

An object of class QFeatures.

i

xxx

with_post_hoc

a character string with 2 possible values: "Yes" and "No" (default) saying if function must perform a Post-Hoc test or not.

post_hoc_test

character string, possible values are "No" (for no test; default value) or TukeyHSD" or "Dunnett". See details of postHocTest() function to choose the appropriate one.

Value

A list of two dataframes. First one called "logFC" contains all pairwise comparisons logFC values (one column for one comparison) for each analysed feature (Except in the case without post-hoc testing, for which NAs are returned.); The second one named "P_Value" contains the corresponding p-values.

Details

This function allows to perform a 1-way Analysis of Variance. Also computes the post-hoc tests if the with_post_hoc parameter is set to yes. There are two possible post-hoc tests: the Tukey Honest Significant Differences (specified as "TukeyHSD") and the Dunnett test (specified as "Dunnett").

See also

postHocTest()

Author

Hélène Borges

Examples

# \donttest{
library(SummarizedExperiment)
data(subR25prot)
obj <- subR25prot
filter <- FunctionFilter('qMetacellOnConditions',
  cmd = 'delete',
  mode = 'AtLeastOneCond',
  pattern = c("Missing POV", "Missing MEC"),
  conds = design.qf(obj)$Condition,
  percent = TRUE,
  th = 0.8,
  operator = '>')
obj <- filterFeaturesOneSE(obj, name = "Filtered", filters = list(filter))
anovatest <- wrapperClassic1wayAnova(obj, 3)
# }