R/tidyMS_R6_Modelling.R
model_analyse.Rdused in project p2901
model_analyse(
pepIntensity,
model_strategy,
subject_Id = "protein_Id",
modelName = "Model"
)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(),
get_p_values_pbeta(),
isSingular_lm(),
linfct_all_possible_contrasts(),
linfct_factors_contrasts(),
linfct_from_model(),
linfct_matrix_contrasts(),
merge_contrasts_results(),
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()
x <- sim_lfq_data_peptide_config()
#> creating sampleName from fileName column
#> Warning: no nr_children column specified in the data, adding column nr_children and setting to 1.
#> completing cases
formula_randomPeptide <-
strategy_lmer("abundance ~ group_ + (1 | peptide_Id)")
mr <- model_analyse( x$data,
formula_randomPeptide,
subject_Id = x$config$table$hierarchy_keys_depth())
#> Warning: There were 4 warnings in `dplyr::mutate()`.
#> The first warning was:
#> ℹ In argument: `linear_model = purrr::map(data, model_strategy$model_fun, pb =
#> pb)`.
#> ℹ In group 2: `protein_Id = "7cbcrd~5725"`.
#> Caused by warning in `value[[3L]]()`:
#> ! WARN :Error: grouping factors must have > 1 sampled level
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 3 remaining warnings.
#> Joining with `by = join_by(protein_Id)`
stopifnot(nrow(get_complete_model_fit(mr$modelProtein)) == 6)