estimateMetricsForAssay {SummarizedBenchmark} | R Documentation

## Estimate performance metrics.

### Description

These functions estimate the performance metrics, either passed as arguments or added previously with the `addPerformanceMetric` function. The function will estimate the performance metric for each method.

### Usage

    estimateMetricsForAssay(object, assay, evalMetric = NULL,
      addColData = FALSE, evalFunction = NULL, tidy = FALSE, ...)

    estimatePerformanceMetrics(object, addColData = FALSE, tidy = FALSE, ...)

### Arguments

`object` | A `SummarizedBenchmark` object.
`assay` | A string with an assay name. Indicates the assay that should be given as input to this performance metric.
`evalMetric` | A string with the name of the evaluation metric.
`addColData` | Logical (default: FALSE). If TRUE, the results are added to the `colData` slot of the `SummarizedExperiment` object and the object is returned. If FALSE, only a `DataFrame` with the results is returned.
`evalFunction` | A function that calculates a performance metric. It should contain at least two arguments, query and truth, where query is the output vector of a method and truth is the vector of ground true values. If additional parameters are specified, they must contain default values. If this parameter is passed, the metrics in the object are ignored and only this evaluation metric is estimated.
`tidy` | Logical (default: FALSE). If TRUE, a long formated `data.frame` is returned.
`...` | Additional parameters passed to the performance functions.

### Value

Either a `SummarizedBenchmark` object, a `DataFrame` or a `data.frame`.

### Functions

- `estimateMetricsForAssay`: Estimate performance metrics for a given assay

- `estimatePerformanceMetrics`: Estimate performance metrics for all assays

### Author(s)

Alejandro Reyes

### Examples

    data( sb )
    sb <- addPerformanceMetric(
       object=sb,
       assay="qvalue",
       evalMetric="TPR",
       evalFunction = function( query, truth, alpha=0.1 ){
           goodHits <- sum( (query < alpha) & truth == 1 )
           goodHits / sum(truth == 1)
       }
    )

    qvalueMetrics <- estimateMetricsForAssay( sb, assay="qvalue" )
    allMetrics <- estimatePerformanceMetrics( sb )
    allMetricsTidy <- estimatePerformanceMetrics( sb, tidy=TRUE )

[Package SummarizedBenchmark version 1.0.4 Index]