| SummarizedBenchmark {SummarizedBenchmark} | R Documentation |
Function to construct SummarizedBenchmark objects.
SummarizedBenchmark(assays, colData, ftData = NULL, groundTruth = NULL, performanceMetrics = NULL, BenchDesign = NULL, ...)
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 |
ftData |
A |
groundTruth |
If present, a |
performanceMetrics |
A |
BenchDesign |
A |
... |
Additional parameters passed to |
A SummarizedBenchmark object.
Alejandro Reyes
## 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 )
colData(sb)$label <- rownames(colData(sb))