Base class for all Contrasts classes

Base class for all Contrasts classes

Methods


Method get_contrast_sides()

get table with sides of the contrast

Usage

ContrastsInterface$get_contrast_sides()


Method get_contrasts()

get table with contrast results (similar to limma topTable function)

Usage

ContrastsInterface$get_contrasts()


Method get_Plotter()

initialize plotter

Usage

ContrastsInterface$get_Plotter()


Method to_wide()

create wide representation of data.

Usage

ContrastsInterface$to_wide()


Method column_description()

column description

Usage

ContrastsInterface$column_description()


Method clone()

The objects of this class are cloneable with this method.

Usage

ContrastsInterface$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

int <- ContrastsInterface$new()
testthat::expect_error(int$get_contrast_sides())
testthat::expect_error(int$get_contrasts())
testthat::expect_error(int$get_Plotter())
testthat::expect_error(int$to_wide())
int$column_description()
#>           column_name
#> modelName   modelName
#> contrast     contrast
#> avgAbd         avgAbd
#> diff             diff
#> FDR               FDR
#> statistic   statistic
#> std.error   std.error
#> df                 df
#> p.value       p.value
#> conf.low     conf.low
#> conf.high   conf.high
#> sigma           sigma
#>                                                                                            description
#> modelName                                                                                type of model
#> contrast                                                      name of difference e.g. group1_vs_group2
#> avgAbd                                                  mean abundance value of protein in all samples
#> diff                                                                       difference among conditions
#> FDR                                                                               false discovery rate
#> statistic                                                                                 t-statistics
#> std.error                                                                               standard error
#> df                                                                                  degrees of freedom
#> p.value                                                                                        p-value
#> conf.low                                                         lower value of 95 confidence interval
#> conf.high                                                         high value of 95 confidence interval
#> sigma     residual standard deviation of linear model (needed for empirical Bayes variance shrinkage).