Nothing
## ----init---------------------------------------------------------------------
library(profileScoreDist)
## ----inr----------------------------------------------------------------------
data(INR)
INR
## ----regularize---------------------------------------------------------------
inr.reg <- regularizeMatrix(INR)
inr.reg
## ----dist params--------------------------------------------------------------
granularity <- 0.05
gcgran <- 0.01
gcmin <- 0.01
gcmax <- 0.99
## gc fractions to consider
gcs <- seq(gcgran*round(gcmin/gcgran), gcgran*round(gcmax/gcgran), gcgran)
## ----dist---------------------------------------------------------------------
## compute probability distributions
distlist <- lapply(gcs, function(x) computeScoreDist(inr.reg, x, granularity))
## ----plot, fig.cap="Reproduction of Figure 1 in the article by Rahmann et al."----
distlist[[50]]
plotDist(distlist[[50]])
## ----cutoffs------------------------------------------------------------------
ab5 <- scoreDistCutoffs(distlist[[50]], 500, 1, c=1, 0.05)
## 5% FDR
ab5$cutoffa
## 5% FNR
ab5$cutoffb
## FDR = FNR
ab5$cutoffopt
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