Extension of the RangedSummarizedExperiment
to
store the output of different methods intended for the same purpose
in a given dataset. For example, a differential expression analysis could be
done using limma-voom, edgeR and DESeq2. The
SummarizedBenchmark class provides a framework that is useful to store, benckmark and
compare results.
performanceMetrics
A SimpleList
of the same length
as the number of assays
containing performance
functions to be compared with the ground truths.
BenchDesign
A BenchDesign
originally used to generate the
results in the object.
#> #>#>#> #>#>#> #>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 )