ContrastsTable: holds results when contrasts are added.

In wolski/prolfqua: Proteomics Label Free Quantification

holds results when contrasts are added.

Description

holds results when contrasts are added.

holds results when contrasts are added.

Super class

prolfqua::ContrastsInterface -> ContrastsTable

Public fields

contrast_result

contrast results

modelName

model name

subject_Id

default protein_Id

Methods

Public methods

• ContrastsTable$new()

• ContrastsTable$get_contrast_sides()

• ContrastsTable$get_linfct()

• ContrastsTable$get_contrasts()

• ContrastsTable$get_Plotter()

• ContrastsTable$to_wide()

• ContrastsTable$clone()

Inherited methods

• prolfqua::ContrastsInterface$column_description()

---

Method new()

intitialize

Usage

ContrastsTable$new(
  contrastsdf,
  subject_Id = "protein_Id",
  modelName = "ContrastTable"
)

Arguments

contrastsdf

data.frame

subject_Id

default protein_Id

modelName

default ContrastTable

---

Method get_contrast_sides()

return sides of contrast

Usage

ContrastsTable$get_contrast_sides()

Returns

data.frame

---

Method get_linfct()

not implemented

Usage

ContrastsTable$get_linfct()

---

Method get_contrasts()

get contrasts

Usage

ContrastsTable$get_contrasts(all = FALSE)

Arguments

all

should all columns be returned (default FALSE)

global

use a global linear function (determined by get_linfct)

---

Method get_Plotter()

get ContrastsPlotter

Usage

ContrastsTable$get_Plotter(FCthreshold = 1, FDRthreshold = 0.1)

Arguments

FCthreshold

fold change threshold

FDRthreshold

fdr threshold

Returns

ContrastsPlotter

---

Method to_wide()

convert to wide format

Usage

ContrastsTable$to_wide(columns = c("p.value", "FDR"))

Arguments

columns

value column default beta.based.significance

Returns

data.frame

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ContrastsTable$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

summary_ROPECA_median_p.scaled

Other modelling: Contrasts, ContrastsMissing, ContrastsModerated, ContrastsPlotter, ContrastsProDA, ContrastsROPECA, INTERNAL_FUNCTIONS_BY_FAMILY, LR_test(), Model, build_model(), contrasts_fisher_exact(), get_anova_df(), get_complete_model_fit(), get_imputed_contrasts(), get_p_values_pbeta(), 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_model_and_data(), plot_lmer_peptide_noRandom(), plot_lmer_peptide_predictions(), plot_lmer_predicted_interactions(), strategy_lmer(), summary_ROPECA_median_p.scaled()

Examples

bb <- prolfqua_data('data_ionstar')$normalized()
bb$config <- old2new(bb$config)
configur <- bb$config$clone(deep=TRUE)
configur$table$hierarchyDepth <- 2
data <- bb$data
lfqdata <- LFQData$new(data, configur)
Contrasts <- c("dilution.b-a" = "dilution.b - dilution.a",
"dilution.c-e" = "dilution.c - dilution.b")
#ContrastsMissing$debug("get_contrasts")
csi <- ContrastsMissing$new(lfqdata, contrasts = Contrasts)
ctr <- csi$get_contrasts()
csi$subject_Id
xcx <- ContrastsTable$new(ctr, subject_Id = csi$subject_Id, modelName = "TableTest")
xcx$get_contrasts()
xcx$get_Plotter()$volcano()
stopifnot(is.null(xcx$get_contrast_sides()))
stopifnot(is.null(xcx$get_linfct()))
stopifnot(ncol(xcx$to_wide()) == 8)

wolski/prolfqua documentation built on April 27, 2024, 4:09 p.m.