COBRAPerformance-class {iCOBRA} | R Documentation

## `COBRAPerformance` object and constructor

### Description

The `COBRAPerformance` class holds various types of calculated performance measures. Objects from this class are typically generated from `COBRAData` objects by means of the function `calculate_performance`.

### Usage

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

### 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).
`fdrnbr` | A data frame containing observed FDR and the number of features considered to be significant at various adjusted p-value thresholds.
`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).
`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
`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.
`splv` | A character string giving the name of the stratification factor, "none" if the results are not stratified.
`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.
`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.
`deviation` | A data frame containing deviations between observed scores and true scores.
`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.
`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.
`maxsplit` | A numeric value indicating the largest number of levels to retain if the results have been stratified by an annotation.
`corr` | A data frame containing observed (Pearson and Spearman) correlation values between observed and true scores.
`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.

### Value

A `COBRAPerformance` object.

### Author(s)

Charlotte Soneson

### Examples

    ## Empty COBRAPerformance object
    COBRAPerformance()

[Package iCOBRA version 1.22.2 Index]