## ---- message=FALSE------------------------------------------------------ set.seed(93) library(odseq) data("seqs") ## ------------------------------------------------------------------------ library(msa) alig <- msa(seqs) ## ------------------------------------------------------------------------ ground_values <- c(rep(FALSE, 211), rep(TRUE, 100)) outliers <- odseq(alig, distance_metric = "affine", B = 1000) ## ------------------------------------------------------------------------ mean(outliers == ground_values) ## ------------------------------------------------------------------------ library(kebabs) sp <- spectrumKernel(k = 3) mat <- getKernelMatrix(sp, seqs) ## ------------------------------------------------------------------------ outliers_unaligned <- odseq_unaligned(mat, B = 1000, type = "similarity") ## ------------------------------------------------------------------------ mean(outliers_unaligned == ground_values)