extrDNADAC: The Dinucleotide-based Auto Covariance Descriptor
Description
The Dinucleotide-based Auto Covariance Descriptor
Usage
extrDNADAC(x, index = c("Twist", "Tilt"), nlag = 2,
normaliztion = FALSE, customprops = NULL, allprop = FALSE)Arguments
x
the input data, which should be a list or file type.
index
the physicochemical indices, it should be a list and there are 38
different physicochemical indices (Table 1), which the users can choose.
nlag
an integer larger than or equal to 0 and less than or equal to L-2 (L means the length
of the shortest DNA sequence in the dataset). It represents the distance between two dinucleotides.
normaliztion
with this option, the final feature vector will be normalized based
on the total occurrences of all kmers. Therefore, the elements in the feature vectors
represent the frequencies of kmers. The default value of this parameter is False.
customprops
the users can use their own indices to generate the feature vector. It should be a dict,
the key is dinucleotide (string), and its corresponding value is a list type.
allprop
all the 38 physicochemical indices will be
employed to generate the feature vector. Its default value is False.
Details
This function calculates the dinucleotide-based auto covariance descriptor
References
Dong Q, Zhou S, Guan J. A new taxonomy-based protein fold recognition approach based on
autocross-covariance transformation. Bioinformatics, 2009, 25(20): 2655-2662.
Examples
Run this code# NOT RUN {
x = 'GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'
extrDNADAC(x)
# }
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