This function aims at predicting the position of Coding DNA Sequences (CDS) through the use of a Correspondence Analysis (CA) computed on codon composition, this for the three reading frames of a DNA strand.
recstat(seq, sizewin = 90, shift = 30, seqname = "no name")a nucleic acid sequence as a vector of characters
an integer, multiple of 3, giving the length of the sliding window
an integer, multiple of 3, giving the length of the steps between two windows
the name of the sequence
This function returns a list containing the following components:
a single DNA sequence as a vector of characters
length of the sliding window
length of the steps between windows
length of the sequence
name of the sequence
a vector containing the positions of windows starts
a vector containing the reading frame of each window
a vector of stop codons positions in direct strand
a vector of stop codons positions in reverse strand
a vector of start codons positions in direct strand
a vector of start codons positions in reverse strand
a matrix containing codons frequencies for all the windows in the three frames of the direct strand
a matrix containing codons frequencies for all the windows in the three frames of the reverse strand
list of class coa and dudi containing the result of the
CA computed on the codons frequencies in the direct strand
list of class coa and dudi containing the result of the
CA computed on the codons frequencies in the reverse strand
The method is built on the hypothesis that the codon composition of a CDS is biased while it is not the case outside these regions. In order to detect such bias, a CA on codon frequencies is computed on the six possible reading frames of a DNA sequence (three from the direct strand and three from the reverse strand). When there is a CDS in one of the reading frame, it is expected that the CA factor scores observed in this frame (fot both rows and columns) will be significantly different from those in the two others.
The original paper describing recstat is:
Fichant, G., Gautier, C. (1987) Statistical method for predicting protein coding regions in nucleic acid sequences. Comput. Appl. Biosci., 3, 287--295. http://bioinformatics.oxfordjournals.org/content/3/4/287.abstract
# NOT RUN {
ff <- system.file("sequences/ECOUNC.fsa", package = "seqinr")
seq <- read.fasta(ff)
rec <- recstat(seq[[1]], seqname = getName(seq))
# }
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