extractPAAC: Pseudo Amino Acid Composition (PseAAC) Descriptor

Description Usage Arguments Value Note Author(s) References See Also Examples

Description

This function calculates the Pseudo Amino Acid Composition (PseAAC) descriptor (dim: 20 + lambda, default is 50).

Usage

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extractPAAC(x, props = c("Hydrophobicity", "Hydrophilicity",
  "SideChainMass"), lambda = 30, w = 0.05, customprops = NULL)

Arguments

x

A character vector, as the input protein sequence.

props

A character vector, specifying the properties used. 3 properties are used by default, as listed below:

'Hydrophobicity'

Hydrophobicity value of the 20 amino acids

'Hydrophilicity'

Hydrophilicity value of the 20 amino acids

'SideChainMass'

Side-chain mass of the 20 amino acids

lambda

The lambda parameter for the PseAAC descriptors, default is 30.

w

The weighting factor, default is 0.05.

customprops

A n x 21 named data frame contains n customized property. Each row contains one property. The column order for different amino acid types is 'AccNo', 'A', 'R', 'N', 'D', 'C', 'E', 'Q', 'G', 'H', 'I', 'L', 'K', 'M', 'F', 'P', 'S', 'T', 'W', 'Y', 'V', and the columns should also be exactly named like this. The AccNo column contains the properties' names. Then users should explicitly specify these properties with these names in the argument props. See the examples below for a demonstration. The default value for customprops is NULL.

Value

A length 20 + lambda named vector

Note

Note the default 20 * 3 prop values have already been independently given in the function. Users can also specify other (up to 544) properties with the Accession Number in the AAindex data, with or without the default three properties, which means users should explicitly specify the properties to use. For this descriptor type, users need to intelligently evaluate the underlying details of the descriptors provided, instead of using this function with their data blindly. It would be wise to use some negative and positive control comparisons where relevant to help guide interpretation of the results.

Author(s)

Nan Xiao <https://nanx.me>

References

Kuo-Chen Chou. Prediction of Protein Cellular Attributes Using Pseudo-Amino Acid Composition. PROTEINS: Structure, Function, and Genetics, 2001, 43: 246-255.

Kuo-Chen Chou. Using Amphiphilic Pseudo Amino Acid Composition to Predict Enzyme Subfamily Classes. Bioinformatics, 2005, 21, 10-19.

JACS, 1962, 84: 4240-4246. (C. Tanford). (The hydrophobicity data)

PNAS, 1981, 78:3824-3828 (T.P.Hopp & K.R.Woods). (The hydrophilicity data)

CRC Handbook of Chemistry and Physics, 66th ed., CRC Press, Boca Raton, Florida (1985). (The side-chain mass data)

R.M.C. Dawson, D.C. Elliott, W.H. Elliott, K.M. Jones, Data for Biochemical Research 3rd ed., Clarendon Press Oxford (1986). (The side-chain mass data)

See Also

See extractAPAAC for amphiphilic pseudo amino acid composition descriptor.

Examples

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x <- readFASTA(system.file("protseq/P00750.fasta", package = "protr"))[[1]]
extractPAAC(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 3 default properties, 4 properties from the
# AAindex database, and 3 cutomized properties
extractPAAC(
  x,
  customprops = myprops,
  props = c(
    "Hydrophobicity", "Hydrophilicity", "SideChainMass",
    "CIDH920105", "BHAR880101",
    "CHAM820101", "CHAM820102",
    "MyProp1", "MyProp2", "MyProp3"
  )
)

Example output

        Xc1.A         Xc1.R         Xc1.N         Xc1.D         Xc1.C 
   9.07025432   10.07806035    5.54293319    7.30659376    9.57415734 
        Xc1.E         Xc1.Q         Xc1.G         Xc1.H         Xc1.I 
   6.80269074    6.80269074   11.58976941    4.28317565    5.03903018 
        Xc1.L         Xc1.K         Xc1.M         Xc1.F         Xc1.P 
  10.83391488    5.54293319    1.76366056    4.53512716    7.55854527 
        Xc1.S         Xc1.T         Xc1.W         Xc1.Y         Xc1.V 
  12.59757544    6.29878772    3.27536961    6.04683621    7.05464225 
 Xc2.lambda.1  Xc2.lambda.2  Xc2.lambda.3  Xc2.lambda.4  Xc2.lambda.5 
   0.02514092    0.02500357    0.02527773    0.02553159    0.02445265 
 Xc2.lambda.6  Xc2.lambda.7  Xc2.lambda.8  Xc2.lambda.9 Xc2.lambda.10 
   0.02561910    0.02486131    0.02506656    0.02553952    0.02437663 
Xc2.lambda.11 Xc2.lambda.12 Xc2.lambda.13 Xc2.lambda.14 Xc2.lambda.15 
   0.02491262    0.02533803    0.02351915    0.02479912    0.02548431 
Xc2.lambda.16 Xc2.lambda.17 Xc2.lambda.18 Xc2.lambda.19 Xc2.lambda.20 
   0.02478210    0.02513770    0.02457224    0.02543046    0.02500889 
Xc2.lambda.21 Xc2.lambda.22 Xc2.lambda.23 Xc2.lambda.24 Xc2.lambda.25 
   0.02476967    0.02342389    0.02431684    0.02610300    0.02626722 
Xc2.lambda.26 Xc2.lambda.27 Xc2.lambda.28 Xc2.lambda.29 Xc2.lambda.30 
   0.02457082    0.02343049    0.02588823    0.02490463    0.02451951 
        Xc1.A         Xc1.R         Xc1.N         Xc1.D         Xc1.C 
   9.12536927   10.13929919    5.57661456    7.35099191    9.63233423 
        Xc1.E         Xc1.Q         Xc1.G         Xc1.H         Xc1.I 
   6.84402695    6.84402695   11.66019407    4.30920216    5.06964960 
        Xc1.L         Xc1.K         Xc1.M         Xc1.F         Xc1.P 
  10.89974663    5.57661456    1.77437736    4.56268464    7.60447439 
        Xc1.S         Xc1.T         Xc1.W         Xc1.Y         Xc1.V 
  12.67412399    6.33706199    3.29527224    6.08357951    7.09750943 
 Xc2.lambda.1  Xc2.lambda.2  Xc2.lambda.3  Xc2.lambda.4  Xc2.lambda.5 
   0.02472188    0.02515055    0.02559236    0.02588471    0.02419172 
 Xc2.lambda.6  Xc2.lambda.7  Xc2.lambda.8  Xc2.lambda.9 Xc2.lambda.10 
   0.02570312    0.02514005    0.02462544    0.02544711    0.02427250 
Xc2.lambda.11 Xc2.lambda.12 Xc2.lambda.13 Xc2.lambda.14 Xc2.lambda.15 
   0.02462431    0.02510916    0.02335959    0.02501099    0.02525138 
Xc2.lambda.16 Xc2.lambda.17 Xc2.lambda.18 Xc2.lambda.19 Xc2.lambda.20 
   0.02491325    0.02527924    0.02448639    0.02542024    0.02498247 
Xc2.lambda.21 Xc2.lambda.22 Xc2.lambda.23 Xc2.lambda.24 Xc2.lambda.25 
   0.02473118    0.02329787    0.02470748    0.02592993    0.02557742 
Xc2.lambda.26 Xc2.lambda.27 Xc2.lambda.28 Xc2.lambda.29 Xc2.lambda.30 
   0.02469289    0.02360989    0.02570375    0.02473739    0.02436325 

protr documentation built on May 18, 2019, 9:02 a.m.