protr (version 0.3-1)

extractMoreauBroto: Normalized Moreau-Broto Autocorrelation Descriptor

Description

Normalized Moreau-Broto Autocorrelation Descriptor

Usage

extractMoreauBroto(x, props = c("CIDH920105", "BHAR880101", "CHAM820101",
  "CHAM820102", "CHOC760101", "BIGC670101", "CHAM810101", "DAYM780201"),
  nlag = 30L, customprops = NULL)

Arguments

x

A character vector, as the input protein sequence.

props

A character vector, specifying the Accession Number of the target properties. 8 properties are used by default, as listed below: [object Object],[object Object],[object Object],[object Object],[object Object],[object

nlag

Maximum value of the lag parameter. Default is 30.

customprops

A n x 21 named data frame contains n customize property. Each row contains one property. The column order for different amino acid types is 'AccNo', 'A', 'R', 'N', 'D

Value

• A length nlag named vector

Details

This function calculates the normalized Moreau-Broto autocorrelation descriptor (Dim: length(props) * nlag).

References

AAindex: Amino acid index database. http://www.genome.ad.jp/dbget/aaindex.html

Feng, Z.P. and Zhang, C.T. (2000) Prediction of membrane protein types based on the hydrophobic index of amino acids. Journal of Protein Chemistry, 19, 269-275.

Horne, D.S. (1988) Prediction of protein helix content from an autocorrelation analysis of sequence hydrophobicities. Biopolymers, 27, 451-477.

Sokal, R.R. and Thomson, B.A. (2006) Population structure inferred by local spatial autocorrelation: an Usage from an Amerindian tribal population. American Journal of Physical Anthropology, 129, 121-131.

See Also

See extractMoran and extractGeary for Moran autocorrelation descriptors and Geary autocorrelation descriptors.

Examples

x = readFASTA(system.file('protseq/P00750.fasta', package = 'protr'))[[1]]
extractMoreauBroto(x)

myprops = data.frame(AccNo = c("MyProp1", "MyProp2", "MyProp3"),
                     A = c(0.62,  -0.5, 15),  R = c(-2.53,   3, 101),
                     N = c(-0.78,  0.2, 58),  D = c(-0.9,    3, 59),
                     C = c(0.29,    -1, 47),  E = c(-0.74,   3, 73),
                     Q = c(-0.85,  0.2, 72),  G = c(0.48,    0, 1),
                     H = c(-0.4,  -0.5, 82),  I = c(1.38, -1.8, 57),
                     L = c(1.06,  -1.8, 57),  K = c(-1.5,    3, 73),
                     M = c(0.64,  -1.3, 75),  F = c(1.19, -2.5, 91),
                     P = c(0.12,     0, 42),  S = c(-0.18, 0.3, 31),
                     T = c(-0.05, -0.4, 45),  W = c(0.81, -3.4, 130),
                     Y = c(0.26,  -2.3, 107), V = c(1.08, -1.5, 43))

# Use 4 properties in the AAindex database, and 3 cutomized properties
extractMoreauBroto(x, customprops = myprops,
                   props = c('CIDH920105', 'BHAR880101',
                             'CHAM820101', 'CHAM820102',
                             'MyProp1', 'MyProp2', 'MyProp3'))