For more details and references see package vignette
vignette("TargetDecoyFDR_Example", package = "prozor")
computeFDRwithID(score, ID, decoy = "REV_", larger_better = TRUE)
Arguments
| score | a vector with scores |
|---|---|
| ID | - list with protein id's |
| decoy | decoy pattern, default "REV_" |
| larger_better | if larger score better than small (default TRUE), If small score better set FALSE |
Value
list with ID, decoy_hit (indicates if decoy), score the search engine score, FDR1 false discovery rate estimated using the method of Elias and Gygi; FDR2 - estimated using the method of Kell.
Examples
data(fdrSample) # call constructor #nrow(fdrSample) #fdrSample <- dplyr::slice_sample(fdrSample, n = 40000) #usethis::use_data(fdrSample, overwrite = TRUE) fdr1 <- computeFDRwithID(fdrSample$score, fdrSample$proteinID, larger_better = FALSE) names(fdr1) #> [1] "larger_better" "order" "decoy_hit" "score" #> [5] "FPR" "SimpleFDR" "qValue_FPR" "qValue_SimpleFDR" #> [9] "ID" plot(fdr1$score, fdr1$FPR,type="l",xlim=c(0,0.001), ylim=c(0,0.0002)) lines(fdr1$score, fdr1$qValue_FPR, col=2) lines(fdr1$score, fdr1$SimpleFDR,type="l",col=4) lines(fdr1$score, fdr1$qValue_SimpleFDR, col=5)fdr1 <- computeFDRwithID(fdrSample$score2, fdrSample$proteinID, larger_better = TRUE) names(fdr1) #> [1] "larger_better" "order" "decoy_hit" "score" #> [5] "FPR" "SimpleFDR" "qValue_FPR" "qValue_SimpleFDR" #> [9] "ID" plot(fdr1$score, fdr1$FPR,type="l", xlim=c(2.5,5),ylim=c(0,0.001)) lines(fdr1$score, fdr1$qValue_FPR, col=2) lines(fdr1$score, fdr1$SimpleFDR,type="l",col=4) lines(fdr1$score, fdr1$qValue_SimpleFDR, col=5)
