ftrCOOL (version 2.0.0)

AAutoCor: Amino Acid Autocorrelation-Autocovariance (AAutoCor)

Description

It creates the feature matrix for each function in autocorelation (i.e., Moran, Greay, NormalizeMBorto) or autocovariance (i.e., AC, CC,ACC). The user can select any combination of the functions too. In this case, the final matrix will contain features of each selected function.

Usage

AAutoCor(
  seqs,
  selectedAAidx = list(c("CIDH920105", "BHAR880101", "CHAM820101", "CHAM820102",
    "CHOC760101", "BIGC670101", "CHAM810101", "DAYM780201")),
  maxlag = 3,
  threshold = 1,
  type = c("Moran", "Geary", "NormalizeMBorto", "AC", "CC", "ACC"),
  label = c()
)

Arguments

seqs

is a FASTA file with amino acid sequences. Each sequence starts with a '>' character. Also, seqs could be a string vector. Each element of the vector is a peptide/protein sequence.

selectedAAidx

Function takes as input the physicochemical properties. Users select the properties by their ids or indices in the aaIndex2 file. This parameter could be a vector or a list of amino acid indices. The default values of the vector are the 'CIDH920105','BHAR880101','CHAM820101','CHAM820102','CHOC760101','BIGC670101','CHAM810101','DAYM780201' ids in the aaIndex2 file.

maxlag

This parameter shows the maximum gap between two amino acids. The gaps change from 1 to maxlag (the maximum lag).

threshold

is a number between (0 , 1]. In selectedAAidx, indices with a correlation higher than the threshold will be deleted. The default value is 1.

type

could be 'Moran', 'Greay', 'NormalizeMBorto', 'AC', 'CC', or 'ACC'. Also, it could be any combination of them.

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

This function returns a feature matrix. The number of columns in the matrix changes depending on the chosen autocorrelation or autocovariance types and nlag parameter. The output is a matrix. The number of rows shows the number of sequences.

Details

For CC and AAC autocovriance functions, which consider the covariance of the two physicochemical properties, we have provided users with the ability to categorize their selected properties in a list. The binary combination of each group will be taken into account. Note: If all the features are in a group or selectedAAidx parameter is a vector, the binary combination will be calculated for all the physicochemical properties.

Examples

# NOT RUN {
filePrs<-system.file("extdata/proteins.fasta",package="ftrCOOL")
mat1<-AAutoCor(seqs=filePrs,maxlag=20,threshold=0.9,
type=c("Moran","Geary","NormalizeMBorto","AC"))

mat2<-AAutoCor(seqs=filePrs,maxlag=20,threshold=0.9,selectedAAidx=
list(c('CIDH920105','BHAR880101','CHAM820101','CHAM820102'),c('CHOC760101','BIGC670101')
,c('CHAM810101','DAYM780201')),type=c("AC","CC","ACC"))

# }