featureAAindex {BioSeqClass} | R Documentation |
Protein sequences are coded based on the physicochemical/biochemical properties of amino acids in AAindex database.
featureAAindex(seq,aaindex.name="all") featureACI(seq,aaindex.name="all") featureACF(seq,n,aaindex.name="all")
seq |
a string vector for the protein, DNA, or RNA sequences. |
aaindex.name |
a string for the name of physicochemical and biochemical properties in AAindx. |
n |
an integer used as paramter of |
featureAAindex
returns a matrix measuring the physicochemical
and biochemical properties of amino acids by AAindex (http://www.genome.jp/aaindex).
If parameter aaindex.name="all",
all properties in AAindex will be considered, and each row represented the
features of one sequence coding by a 531*N dimension numeric vector. If parameter
aaindex.name is a name of property in AAindex, each row represented the features
of one sequence coding by a N dimension numeric vector.
featureACI
returns a matrix with 531 columns, measuring the
average cumulative value of AAindex. N is the length of input sequence, and
N must be odd. Central residue of all windows are the central residue of input
sequence. Each column is the average cumulative AAindex over a sliding window.
featureACF
returns a matrix with 531*n columns, measuring the
Auto-Correlation Function (ACF) of AAindex. If parameter aaindex.name is a name
of property in AAindex, each row represented the features of one sequence coding
by a n dimension numeric vector.
Hong Li
if(interactive()){ file = file.path(path.package("BioSeqClass"), "example", "acetylation_K.pos40.pep") seq = as.matrix(read.csv(file,header=F,sep="\t",row.names=1))[,1] AI_all = featureAAindex(seq) AI_ANDN920101 = featureAAindex(seq,"ANDN920101") ACI_all = featureACI(seq) ACI_ANDN920101 = featureACI(seq,"ANDN920101") ACF_all_1 = featureACF(seq,1) ACF_ANDN920101_3 = featureACF(seq,3,"ANDN920101") }