R/tidyMS_R6_Modelling.R
get_p_values_pbeta.Rd
p-value of protein from p.value of the median fold change peptide.
get_p_values_pbeta(median.p.value, n.obs, max.n = 10)
limit number of peptides per protein.
Other modelling:
Contrasts
,
ContrastsMissing
,
ContrastsModerated
,
ContrastsPlotter
,
ContrastsProDA
,
ContrastsROPECA
,
ContrastsTable
,
INTERNAL_FUNCTIONS_BY_FAMILY
,
LR_test()
,
Model
,
build_model()
,
contrasts_fisher_exact()
,
get_anova_df()
,
get_complete_model_fit()
,
isSingular_lm()
,
linfct_all_possible_contrasts()
,
linfct_factors_contrasts()
,
linfct_from_model()
,
linfct_matrix_contrasts()
,
merge_contrasts_results()
,
model_analyse()
,
model_summary()
,
moderated_p_limma()
,
moderated_p_limma_long()
,
my_contest()
,
my_contrast()
,
my_contrast_V1()
,
my_contrast_V2()
,
my_glht()
,
pivot_model_contrasts_2_Wide()
,
plot_lmer_peptide_predictions()
,
sim_build_models_lm()
,
sim_build_models_lmer()
,
sim_make_model_lm()
,
sim_make_model_lmer()
,
strategy_lmer()
,
summary_ROPECA_median_p.scaled()
plot(get_p_values_pbeta(0.1,1:10,10), ylim=c(0,0.1))
plot(get_p_values_pbeta(0.1,1:10,3), ylim=c(0,0.1))
plot(get_p_values_pbeta(0.3,1:30, 3), ylim=c(0,0.1))
abline(h=.05,col = 2)
plot(seq(0.0,1.0,length=30),get_p_values_pbeta(seq(0.0,1.0,length=30),rep(10,30)))
abline(0,1)
plot(seq(0.0,1.0,length=30),get_p_values_pbeta(seq(0.0,1.0,length=30),rep(10,30),3))
abline(0,1)
testthat::expect_equal(get_p_values_pbeta(0.3,10, 3),0.216, tolerance = 1e-4)
testthat::expect_equal(get_p_values_pbeta(0,10, 3),0, tolerance = 1e-4)
testthat::expect_equal(get_p_values_pbeta(1,10, 3),1, tolerance = 1e-4)
testthat::expect_equal(get_p_values_pbeta(1,10, 3),get_p_values_pbeta(1,3, 10), tolerance = 1e-4)