ftrCOOL (version 2.0.0)

NCP_RNA: riboNucleotide Chemical Property (NCP_RNA)

Description

This function replaces ribonucleotides with a three-length vector. The vector represent the ribonucleotides such that 'A' will be replaced with c(1, 1, 1), 'C' with c(0, 1, 0),'G' with c(1, 0, 0), and 'U' with c(0, 0, 1).

Usage

NCP_RNA(
  seqs,
  binaryType = "numBin",
  outFormat = "mat",
  outputFileDist = "",
  label = c()
)

Arguments

seqs

is a FASTA file containing ribonucleotide sequences. The sequences start with '>'. Also, seqs could be a string vector. Each element of the vector is a ribonucleotide sequence.

binaryType

It can take any of the following values: ('strBin','logicBin','numBin'). 'strBin'(String binary): each ribonucleotide is represented by a string containing 4 characters(0-1). A = "0001" , C = "0010" , G = "0100" , T = "1000" 'logicBin'(logical value): Each ribonucleotide is represented by a vector containing 4 logical entries. A = c(F,F,F,T) , ... , T = c(T,F,F,F) 'numBin' (numeric bin): Each ribonucleotide is represented by a numeric (i.e., integer) vector containing 4 numerals. A = c(0,0,0,1) , ... , T = c(1,0,0,0)

outFormat

(output format) can take two values: 'mat'(matrix) and 'txt'. The default value is 'mat'.

outputFileDist

shows the path and name of the 'txt' output file.

label

is an optional parameter. It is a vector whose length is equivalent to the number of sequences. It shows the class of each entry (i.e., sequence).

Value

The output is different depending on the outFormat parameter ('mat' or 'txt'). If outFormat is set to 'mat', it returns a feature matrix for sequences with the same lengths. The number of rows is equal to the number of sequences and if binaryType is 'strBin', the number of columns is the length of the sequences. Otherwise, it is equal to (length of the sequences)*3. If outFormat is 'txt', all binary values will be written to a tab-delimited file. Each line in the file shows the binary format of a sequence.

References

Chen, Zhen, et al. "iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data." Briefings in bioinformatics 21.3 (2020): 1047-1057.

Examples

# NOT RUN {
dir = tempdir()
fileLNC<-system.file("extdata/Carica_papaya101RNA.txt",package="ftrCOOL")
mat<-NCP_RNA(seqs = fileLNC,binaryType="strBin",outFormat="mat")

ad<-paste0(dir,"/NCP.txt")
NCP_RNA(seqs = fileLNC,binaryType="numBin",outFormat="txt",outputFileDist=ad)
unlink("dir", recursive = TRUE)
# }