COBRAPlot-class {iCOBRA} | R Documentation

## `COBRAPlot` object and constructor

### Description

The `COBRAPlot` class is similar to the `COBRAPerformance` class in that it holds various types of calculated performance measures. However, it also contains other attributes that are necessary for plotting, such as color assignments. Several `COBRAPlot` objects can be generated from the same `COBRAPerformance` object, without having to go through the potentially time consuming task of recalculating all performance measures. Objects from this class are typically generated from a `COBRAPerformance` objects by means of the function `prepare_data_for_plot`.

### Usage

    COBRAPlot(fdrtpr = data.frame(), fdrtprcurve = data.frame(),
      fsrnbr = data.frame(), fsrnbrcurve = data.frame(),
      fdrnbr = data.frame(), corr = data.frame(), fdrnbrcurve = data.frame(),
      tpr = data.frame(), fpr = data.frame(), roc = data.frame(),
      scatter = data.frame(), onlyshared = NA, fpc = data.frame(),
      overlap = data.frame(), plotcolors = "", splv = "",
      deviation = data.frame(), maxsplit = NA_integer_, facetted = NA)

### Arguments

`fdrtpr` | A data frame containing observed FDR and TPR values at various adjusted p-value thresholds.
`fdrtprcurve` | A data frame containing observed FDR and TPR values for a (potentially large) number of cutoffs applied to a 'score' (that can be p-value, adjusted p-value or a more general score).
`fsrnbr` | A data frame containing observed false sign rate (FSR) and the number of features considered to be significant at various s-value thresholds
`fsrnbrcurve` | A data frame containing observed false sign rate (FSR) and number of features considered to be significant for a (potentially large) number of cutoffs applied to the s-value
`fdrnbr` | A data frame containing observed FDR and the number of features considered to be significant at various adjusted p-value thresholds.
`corr` | A data frame containing observed (Pearson and Spearman) correlation values between observed and true scores.
`fdrnbrcurve` | A data frame containing observed FDR and number of features considered to be significant for a (potentially large) number of cutoffs applied to a 'score' (that can be p-value, adjusted p-value or a more general score).
`tpr` | A data frame containing observed TPR values at various adjusted p-value thresholds.
`fpr` | A data frame containing observed FPR values at various adjusted p-value thresholds.
`roc` | A data frame containing observed FPR and TPR values for a (potentially large) number of cutoffs applied to a 'score' (that can be p-value, adjusted p-value or a more general score), which can be used to generate a ROC curve.
`scatter` | A data frame containing observed 'scores' (p-values, adjusted p-values or more general scores) and true scores, which can be used to generate scatter plots.
`onlyshared` | A logical value indicating whether only features shared between the results and the truth should be retained, or if all features present in the truth should be used.
`fpc` | A data frame containing observed numbers of false positive findings among the N top-ranked features (ranked by p-values, adjusted p-values or more general scores), for a (potentially large) number of Ns, which can be used to generate a false positive curve.
`overlap` | A data frame or list of data frames with binary values indicating, for each of a number of methods and number of features, whether the method consider the feature 'positive' (significant, 1) or 'negative' (non-significant, 0). If it is a list of data frames, each list element corresponds to one level of a stratifying factor.
`plotcolors` | A character vector giving the color for each method (or method-stratification level combination).
`splv` | A character string giving the name of the stratification factor, "none" if the results are not stratified.
`deviation` | A data frame containing deviations between observed scores and true scores.
`maxsplit` | A numeric value indicating the largest number of levels to retain if the results have been stratified by an annotation.
`facetted` | A logical indicating whether the data is prepared for a facetted plot (separating different stratification levels into different panels) or for displaying all values in one plot panel.

### Value

A `COBRAPlot` object.

### Author(s)

Charlotte Soneson

### Examples

    ## Empty COBRAPlot object
    cobraplot <- COBRAPlot()

[Package iCOBRA version 1.16.0 Index]