## ----echo=FALSE, include=FALSE---------------------------------------------
knitr::opts_chunk$set(tidy = FALSE, cache = TRUE, dev = "png",
                      message = FALSE, error = FALSE, warning = TRUE)

## --------------------------------------------------------------------------
library("SummarizedBenchmark")
library("magrittr")

## --------------------------------------------------------------------------
data(tdat)

## --------------------------------------------------------------------------
head(tdat)

## --------------------------------------------------------------------------
adj_bonf <- p.adjust(p = tdat$pval, method = "bonferroni")

adj_bh <- p.adjust(p = tdat$pval, method = "BH")

qv <- qvalue::qvalue(p = tdat$pval)
adj_qv <- qv$qvalues

## --------------------------------------------------------------------------
adj <- cbind.data.frame(adj_bonf, adj_bh, adj_qv)
head(adj)

## --------------------------------------------------------------------------
b <- BenchDesign(data = tdat)

## --------------------------------------------------------------------------
b <- addMethod(bd = b, label = "bonf", func = p.adjust,
               params = rlang::quos(p = pval, method = "bonferroni"))

## --------------------------------------------------------------------------
b <- b %>% 
    addMethod(label = "BH",
              func = p.adjust,
              params = rlang::quos(p = pval, method = "BH")) %>%
    addMethod(label = "qv",
              func = qvalue::qvalue,
              params = rlang::quos(p = pval),
              post = function(x) { x$qvalues })

## --------------------------------------------------------------------------
b

## --------------------------------------------------------------------------
printMethods(b)

## --------------------------------------------------------------------------
sb <- buildBench(b, truthCols = "H")

## --------------------------------------------------------------------------
head(assay(sb))

## --------------------------------------------------------------------------
colData(sb)

## --------------------------------------------------------------------------
rowData(sb)

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

performanceMetrics(sb)[["H"]]

## --------------------------------------------------------------------------
resWide <- estimatePerformanceMetrics(sb, alpha = c(0.05, 0.1, 0.2))
resWide

## ----elWide----------------------------------------------------------------
elementMetadata(resWide)

## --------------------------------------------------------------------------
sb <- estimatePerformanceMetrics(sb, 
                                 alpha = c(0.05, 0.1, 0.2), 
                                 addColData = TRUE)
colData(sb)
elementMetadata(colData(sb))

## --------------------------------------------------------------------------
estimatePerformanceMetrics(sb, 
                           alpha = c(0.05, 0.1, 0.2), 
                           tidy = TRUE)

## --------------------------------------------------------------------------
head(tidyUpMetrics(sb))

## --------------------------------------------------------------------------
tidyUpMetrics(sb) %>%
  dplyr:::filter(label == "bonf", alpha == 0.1, performanceMetric == "TPR") %>%
  dplyr:::select(value)