View source: R/PhysicochemicalProperty.R
computePhysChem_AAindex | R Documentation |
The function computePhysChem_AAindex
computes the physicochemical features of
protein sequences with the help of AAindex provided by aaindex
from seqinr-package
.
computePhysChem_AAindex(
seqPro,
entry.index = NULL,
Fourier.len = 10,
parallel.cores = 2,
cl = NULL
)
seqPro |
protein sequences loaded by function |
entry.index |
The entry number of AAindex. For example the entry number of "Kyte & Doolittle Hydrophaty"
index is 151, and the entry number of "Hopp-Woods Hydrophilicity" is 115. Thus,
the corresponding |
Fourier.len |
positive integer specifying the Fourier series length that will be used as features.
The |
parallel.cores |
an integer that indicates the number of cores for parallel computation. Default: |
cl |
parallel cores to be passed to this function. |
This function returns a data frame.
[1] Kawashima S, Kanehisa M. AAindex: amino acid index database. Nucleic Acids Res. 2000; 28:374
[2] Charif D, Lobry JR. SeqinR 1.0-2: a contributed package to the R project for statistical computing devoted to biological sequences retrieval and analysis. In: Structural approaches to sequence evolution: Molecules, networks, populations. 2007; 207-232
computePhysChem
, aaindex
data(demoPositiveSeq)
seqs <- demoPositiveSeq$Pro.positive
data(aaindex, package = "seqinr")
# Check the aaindex list provided by package "seqinr":
?seqinr::aaindex
# Supose that we need "Kyte & Doolittle Hydrophaty" index,
# and we can find the entries with Kyte as author:
which(sapply(aaindex, function(x) length(grep("Kyte", x$A)) != 0))
# This returns entry number 151.
# And 151 is the "entry.index" used by this function.
# Users can also obtain the entry number by retrieving information in other
# fields such as "x$D" (Data description) or "x$T" (Title of the article).
# See documentation of "seqinr::aaindex" for detailed information.
feature_aaindex_1 <- computePhysChem_AAindex(seqPro = seqs, entry.index = 151,
Fourier.len = 10, parallel.cores = 2)
# If you need to compute features with more than aaindex data:
feature_aaindex_2 <- computePhysChem_AAindex(seqPro = seqs, entry.index = c(151, 68),
Fourier.len = 10, parallel.cores = 2)
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