Applies a statistical test on each element of a list of linear models

Usage

testAnovaModels(aov_fits, test = "Omnibus")

Arguments

aov_fits: a list of linear models, such as those outputted by applyAnovasOnProteins
test: a character string among "Omnibus", "TukeyHSD", "TukeySinglestep", "TukeyStepwise", "TukeyNoMTC", "DunnettSinglestep", "DunnettStepwise" and "DunnettNoMTC". "Omnibus" tests the all-mean equality, the Tukey tests compares all pairs of means and the Dunnet tests compare all the means to the first one. For multiple tests (Dunnet's or Tukey's) it is possible to correct for multiplicity (either with single-step or step-wise FWER) or not. All the Tukey's and Dunnet's tests use the multcomp package expect for "TukeyHSD" which relies on the stats package. "TukeyHSD" and "TukeyStepwise" gives similar results.

Value

a list of 2 tables (p-values and fold-changes, respecively)

Author

Thomas Burger

Examples

data(Exp1_R25_prot, package='DaparToolshedData')
exdata <- Exp1_R25_prot[1:5,]
testAnovaModels(applyAnovasOnProteins(exdata, 1))
#> $logFC
#>                                                anova_1way_logFC
#> CON__A2I7N1;CON__A2I7N0                                      NA
#> CON__P00761                                                  NA
#> P02768upsedyp|ALBU_HUMAN_upsedyp;CON__P02768-1               NA
#> CON__P04264                                                  NA
#> CON__P07477                                                  NA
#> 
#> $P_Value
#>                                                anova_1way_pval
#> CON__A2I7N1;CON__A2I7N0                           4.325725e-01
#> CON__P00761                                       8.916825e-01
#> P02768upsedyp|ALBU_HUMAN_upsedyp;CON__P02768-1    2.052406e-05
#> CON__P04264                                       5.013337e-02
#> CON__P07477                                       8.704512e-01
#>