extrDNADCC: The Dinucleotide-based Cross Covariance Descriptor

In BioMedR: Generating Various Molecular Representations for Chemicals, Proteins, DNAs, RNAs and Their Interactions

Description

The Dinucleotide-based Cross Covariance Descriptor

Usage

extrDNADCC(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 cross covariance descriptor

Value

A vector

Note

if the user defined physicochemical indices have not been normalized, it should be normalized.

Author(s)

Min-feng Zhu <[e-mail]>

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.

See Also

See extrDNADAC and extrDNADACC

Examples

 
x = 'GACTGAACTGCACTTTGGTTTCATATTATTTGCTC'
extrDNADCC(x)

BioMedR documentation built on July 5, 2019, 9:03 a.m.