permutation_test_plot {AlpsNMR} | R Documentation

## Permutation test plot

### Description

Plot permutation test using actual model and permutated models

### Usage

    permutation_test_plot(
      nmr_data_analysis_model,
      permMatrix,
      xlab = "AUCs",
      xlim,
      ylim = NULL,
      breaks = "Sturges",
      main = "Permutation test"
    )

### Arguments

`nmr_data_analysis_model` | A nmr_data_analysis_model
`permMatrix` | A permutation fitness outcome from permutation_test_model
`xlab` | optional xlabel
`xlim` | optional x-range
`ylim` | otional y-range
`breaks` | optional custom histogram breaks (defaults to 'sturges')
`main` | optional plot title (or TRUE for autoname)

### Value

A plot with the comparison between the actual model versus the permuted models

### Examples

    # Data analysis for a table of integrated peaks

    ## Generate an artificial nmr_dataset_peak_table:
    ### Generate artificial metadata:
    num_samples <- 32 # use an even number in this example
    num_peaks <- 20
    metadata <- data.frame(
        NMRExperiment = as.character(1:num_samples),
        Condition = rep(c("A", "B"), times = num_samples/2),
        stringsAsFactors = FALSE
    )

    ### The matrix with peaks
    peak_means <- runif(n = num_peaks, min = 300, max = 600)
    peak_sd <- runif(n = num_peaks, min = 30, max = 60)
    peak_matrix <- mapply(function(mu, sd) rnorm(num_samples, mu, sd),
                                                mu = peak_means, sd = peak_sd)
    colnames(peak_matrix) <- paste0("Peak", 1:num_peaks)

    ## Artificial differences depending on the condition:
    peak_matrix[metadata$Condition == "A", "Peak2"] <-
        peak_matrix[metadata$Condition == "A", "Peak2"] + 70

    peak_matrix[metadata$Condition == "A", "Peak6"] <-
        peak_matrix[metadata$Condition == "A", "Peak6"] - 60

    ### The nmr_dataset_peak_table
    peak_table <- new_nmr_dataset_peak_table(
        peak_table = peak_matrix,
        metadata = list(external = metadata)
    )

    methodology <- plsda_auroc_vip_method(ncomp = 3)
    model <- nmr_data_analysis(
        peak_table,
        y_column = "Condition",
        identity_column = NULL,
        external_val = list(iterations = 3, test_size = 0.25),
        internal_val = list(iterations = 3, test_size = 0.25),
        data_analysis_method = methodology
    )

    p = permutation_test_model(peak_table,
                               y_column = "Condition",
                               identity_column = NULL,
                               external_val = list(iterations = 3, test_size = 0.25),
                               internal_val = list(iterations = 3, test_size = 0.25),
                               data_analysis_method = methodology,
                               nPerm = 10)

    permutation_test_plot(model, p)

[Package AlpsNMR version 3.2.3 Index]