Description Usage Arguments Details Value Note See Also Examples
View source: R/run_signalHsmm.R
Using the hidden semi-Markov model predict presence of signal peptide in eukaryotic proteins.
1 | run_signalHsmm(test_data)
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test_data |
single protein sequence ( |
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.
An object of class hsmm_pred_list
.
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | #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]])
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