SummarizedBenchmark {SummarizedBenchmark} | R Documentation

## Constructor function for SummarizedBenchmark objects.

### Description

Function to construct `SummarizedBenchmark` objects.

### Usage

    SummarizedBenchmark(assays, colData, ftData = NULL, groundTruth = NULL,
      performanceMetrics = NULL, ...)

### Arguments

`assays` | A list containing outputs of the methods to be benchmark. Each element of the list must contain a matrix or data.frame of n x m, n being the number of features tested (e.g. genes) and m being the number of methods in the benchmark. Each element of the list must contain a single assay (the outputs of the methods). For example, for a benchmark of differential expression methods, one assay could contain the q-values from the different methods and another assay could be the estimated log fold changes.
`colData` | A `DataFrame` describing the annotation of the methods. These could include version of the software or the parameters used to run them.
`ftData` | A `DataFrame` object describing the rows. This parameter is equivalent to the parameter rowData of a SummarizedExperiment.
`groundTruth` | If present, a `DataFrame` containing the ground truths. If provided, the number of columns must be the same as the number of assays (NA's are accepted). The names of the columns should have the same names as the assays.
`performanceMetrics` | A `SimpleList` of the same length as the number of assays. Each element of the list must be a list of functions. Each function must contain the parameters 'query' and 'truth'.
`...` | Additional parameters passed to `SummarizedExperiment`.

### Value

A `SummarizedBenchmark` object.

### Author(s)

Alejandro Reyes

### Examples

    ## loading the example data from iCOBRA
    library(iCOBRA)
    data(cobradata_example)

    ## a bit of data wrangling and reformatting
    assays <- list(
        qvalue=cobradata_example@padj,
        logFC=cobradata_example@score )
    assays[["qvalue"]]$DESeq2 <- p.adjust(cobradata_example@pval$DESeq2, method="BH")
    groundTruth <- DataFrame( cobradata_example@truth[,c("status", "logFC")] )
    colnames(groundTruth) <- names( assays )
    colData <- DataFrame( method=colnames(assays[[1]]) )
    groundTruth <- groundTruth[rownames(assays[[1]]),]

    ## constructing a SummarizedBenchmark object
    sb <- SummarizedBenchmark(
        assays=assays, colData=colData,
        groundTruth=groundTruth )

[Package SummarizedBenchmark version 1.0.4 Index]