run_signalHsmm {signalHsmm} | R Documentation |
Predict presence of signal peptide in protein
Description
Using the hidden semi-Markov model predict presence of signal peptide in eukaryotic proteins.
Usage
run_signalHsmm(test_data)
Arguments
test_data |
single protein sequence ( |
Details
Function signalHsmm
returns respectively probability of presence of
signal peptide, start of signal peptide and the probable cleavage site localization.
If input consists of more than one sequence, result is a data.frame where each column
contains above values for different proteins.
Value
An object of class hsmm_pred_list
.
Note
Currently start of signal peptide is naively set as 1 amino acid. The prediction of a cleavage site is still an experimental feature, use on your own risk.
See Also
Examples
#run signalHsmm on one sequence
x1 <- run_signalHsmm(benchmark_dat[[1]])
#run signalHsmm on one sequence, but input is a character vector
x2 <- run_signalHsmm(c("M", "A", "G", "K", "E", "V", "I", "F", "I", "M", "A", "L",
"F", "I", "A", "V", "E", "S", "S", "P", "I", "F", "S", "F", "D",
"D", "L", "V", "C", "P", "S", "V", "T", "S", "L", "R", "V", "N",
"V", "E", "K", "N", "E", "C", "S", "T", "K", "K", "D", "C", "G",
"R", "N", "L", "C", "C", "E", "N", "Q", "N", "K", "I", "N", "V",
"C", "V", "G", "G", "I", "M", "P", "L", "P", "K", "P", "N", "L",
"D", "V", "N", "N", "I", "G", "G", "A", "V", "S", "E", "S", "V",
"K", "Q", "K", "R", "E", "T", "A", "E", "S", "L"))
#run signalHsmm on list of sequences
x3 <- run_signalHsmm(benchmark_dat[1:3])
#see summary of results
summary(x3)
#print results as data frame
pred2df(x3)
#summary one result
summary(x3[[1]])
plot(x3[[1]])
[Package signalHsmm version 1.5 Index]