computeStructure | R Documentation |
The function computeStructure
computes the secondary structural features of RNA
or protein sequences. ViennaRNA package and Predator is required.
computeStructure(
seqs,
seqType = c("RNA", "Pro"),
args.RNAsubopt = NULL,
args.Predator = NULL,
structureRNA.num = 6,
structurePro = c("ChouFasman", "DeleageRoux", "Levitt"),
Fourier.len = 10,
workDir.Pro = getwd(),
as.list = TRUE,
path.RNAsubopt = "RNAsubopt",
path.Predator = "Predator/predator",
path.stride = "Predator/stride.dat",
verbose = FALSE,
parallel.cores = 2,
cl = NULL
)
seqs |
sequences loaded by function |
seqType |
a string that specifies the nature of the sequence: |
args.RNAsubopt |
string (in format such as "-N -z -S 1.07") specifying additional arguments (except "-p" which is already determined by structureRNA.num) for RNAsubopt. This is used when you want to control the behaviour of RNAsubopt. Arguments for RNAsubopt please refer to its manual. Default: |
args.Predator |
string specifying additional arguments (except "-a" and "-b") for Predator. This is used when you want to control the behaviour of Predator. Arguments for Predator please refer to its manual. Default: |
structureRNA.num |
integer. The number of random samples of suboptimal structures. Default: |
structurePro |
strings specifying the secondary structural information that are extracted from protein sequences.
Ignored if |
Fourier.len |
positive integer specifying the Fourier series length that will be used as features.
The |
workDir.Pro |
string specifying the directory for temporary files. The temp files will be deleted automatically when the calculation is completed. |
as.list |
logical. The result will be returned as a list or data frame. |
path.RNAsubopt |
string specifying the location of RNAsubopt program. (Ref: [5]) |
path.Predator |
string specifying the location of Predator program. (Ref: [6]) |
path.stride |
string specifying the location of file "stride.dat" required by program Predator. |
verbose |
logical. Should the relevant information be printed during the calculation? (Only available on Linux.) |
parallel.cores |
an integer that indicates the number of cores for parallel computation. Default: |
cl |
parallel cores to be passed to this function. |
The secondary structures of RNA and protein are computed by RNAsubopt and Predator, respectively. And the protein secondary features are encoded using three amino acid scales:
Chou & Fasman conformational parameter (Ref: [2])
Deleage & Roux conformational parameter (Ref: [3])
Levitt normalised frequency (Ref: [4])
The feature encoding strategy is based on lncPro (Ref: [7]).
This function depends on the program "RNAsubopt" of software "ViennaRNA" (http://www.tbi.univie.ac.at/RNA/index.html) and "Predator" (https://bioweb.pasteur.fr/packages/pack@predator@2.1.2).
Parameter path.RNAsubopt
can be simply defined as "RNAsubopt"
as
default when the OS is UNIX/Linux. However, for some OS, such as Windows, users may
need to specify the path.RNAsubopt
if the path of "RNAsubopt" haven't been
added in environment variables (e.g. path.RNAsubopt = '"C:/Program Files/ViennaRNA/RNAsubopt.exe"'
).
Program "Predator" is only available on UNIX/Linux and 32-bit Windows OS.
This function returns a data frame if as.list = FALSE
or returns a list if as.list = TRUE
.
[1] Han S, Yang X, Sun H, et al. LION: an integrated R package for effective prediction of ncRNA–protein interaction. Briefings in Bioinformatics. 2022; 23(6):bbac420
[2] Chou PY, Fasman GD. Prediction of the secondary structure of proteins from their amino acid sequence. Adv. Enzymol. Relat. Areas Mol. Biol. 1978; 47:45-148
[3] Deleage G, Roux B. An algorithm for protein secondary structure prediction based on class prediction. Protein Eng. Des. Sel. 1987; 1:289-294
[4] Levitt M. Conformational preferences of amino acids in globular proteins. Biochemistry 1978; 17:4277-85
[5] Frishman D, Argos P. Incorporation of non-local interactions in protein secondary structure prediction from the amino acid sequence. Protein Eng. 1996; 9:133-42
[6] Lorenz R, Bernhart SH, Honer zu Siederdissen C, et al. ViennaRNA Package 2.0. Algorithms Mol. Biol. 2011; 6:26
[7] Lu Q, Ren S, Lu M, et al. Computational prediction of associations between long non-coding RNAs and proteins. BMC Genomics 2013; 14:651
runRNAsubopt
, runPredator
, featureStructure
data(demoPositiveSeq)
seqsRNA <- demoPositiveSeq$RNA.positive
seqsPro <- demoPositiveSeq$Pro.positive
# You need to use your own paths:
path.Predator <- "/mnt/external_drive_1/hansy/predator/predator"
path.stride <- "/mnt/external_drive_1/hansy/predator/stride.dat"
structureRNA <- computeStructure(seqsRNA, seqType = "RNA", structureRNA.num = 6,
Fourier.len = 10, as.list = FALSE,
path.RNAsubopt = "RNAsubopt", parallel.cores = 2)
structurePro <- computeStructure(seqsPro, seqType = "Pro",
structurePro = c("ChouFasman", "DeleageRoux",
"Levitt"),
Fourier.len = 10, workDir.Pro = getwd(),
as.list = TRUE, path.Predator = path.Predator,
path.stride = path.stride, parallel.cores = 2)
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