run_signalHsmm: Predict presence of signal peptide in protein
In michbur/signalHsmm: Predict Presence of Signal Peptides

Description Usage Arguments Details Value Note See Also Examples

Using the hidden semi-Markov model predict presence of signal peptide in eukaryotic proteins.

1	run_signalHsmm(test_data)

test_data

single protein sequence (character vector) or list of sequences. It may be an object of class SeqFastaAA.

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.

hsmm_pred_list hsmm_pred

#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]])