convert.reu13.df.to.list(reu13.df) convert.y.to.list(y) convert.n.to.list(n)
convert.y.to.scuo(y) convert.seq.data.to.string(seq.data)
codon.low2up(x) codon.up2low(x)
dna.low2up(x) dna.up2low(x)
convert.b.to.bVec(b) convert.bVec.to.b(bVec, aa.names, model = .CF.CT$model[1])
reu13.df
data frames
divided by amino acids.y
data frames divided by amino acids.n
vectors divided by amino acids.seq.data
format.b
object.bVec
object.convert.reu13.df.to.list()
, convert.y.to.list()
, and
convert.n.to.list()
:
these utility functions take the inputs divided by amino acids
and return the outputs divided by ORFs. convert.y.scuo()
converts y
into scuo
format.
convert.seq.data.to.string()
converts seq.data
into
seq.string
format.
codon.low2up()
and codon.up2low()
convert codon strings
between lower or upper cases.
convert.bVec.to.b()
and convert.b.to.bVec()
convert
objects b
and bVec
.
rearrange.n()
,
rearrange.reu13.df()
,
rearrange.y()
, and
read.seq()
.
## Not run:
# suppressMessages(library(cubfits, quietly = TRUE))
#
# reu13.list <- convert.reu13.df.to.list(ex.train$reu13.df)
# y.list <- convert.y.to.list(ex.train$y)
# n.list <- convert.n.to.list(ex.train$n)
#
# scuo <- convert.y.to.scuo(ex.train$y)
#
# seq.data <- read.seq(get.expath("seq_200.fasta"))
# seq.string <- convert.seq.data.to.string(seq.data)
#
# codon.low2up("acg")
# codon.up2low("ACG")
#
# dna.low2up(c("a", "c", "g"))
# dna.up2low(c("A", "C", "G"))
# ## End(Not run)
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