## ---- 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)