signalHsmm (version 1.5)

run_signalHsmm: 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 (character vector) or list of sequences. It may be an object of class SeqFastaAA.

Value

An object of class hsmm_pred_list.

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.

See Also

hsmm_pred_list hsmm_pred

Examples

# NOT RUN {
#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]])
# }