## Not run:
# rm(list = ls())
# library(cubfits, quietly = TRUE)
#
# y <- ex.train$y
# y.list <- convert.y.to.list(y)
# CAI <- calc_cai_values(y, y.list)$CAI
# plot(CAI, log10(ex.train$phi.Obs), main = "Expression vs CAI",
# xlab = "CAI", ylab = "Expression (log10)")
#
# ### Verify with the seqinr example.
# library(seqinr, quietly = TRUE)
# inputdatfile <- system.file("sequences/input.dat", package = "seqinr")
# input <- read.fasta(file = inputdatfile, forceDNAtolower = FALSE)
# names(input)[65] <- paste(names(input)[65], ".1", sep = "") # name duplicated.
# input <- input[order(names(input))]
#
# ### Convert to cubfits format.
# seq.string <- convert.seq.data.to.string(input)
# new.y <- gen.y(seq.string)
# new.y.list <- convert.y.to.list(new.y)
# ret <- calc_cai_values(new.y, new.y.list)
#
# ### Rebuild w.
# w <- rep(1, 64)
# names(w) <- codon.low2up(rownames(caitab))
# for(i in 1:64){
# id <- which(names(ret$w) == names(w)[i])
# if(length(id) == 1){
# w[i] <- ret$w[id]
# }
# }
# CAI.res <- sapply(input, seqinr::cai, w = w)
#
# ### Plot.
# plot(CAI.res, ret$CAI,
# main = "Comparison of seqinR and cubfits results",
# xlab = "CAI from seqinR", ylab = "CAI from cubfits", las = 1)
# abline(c(0, 1))
# ## End(Not run)
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