#!/usr/bin/env python
from SOAPpy import WSDL

#connect to the SubLoc SOAP server via the WSDL file
wsdl = 'http://www.bioinfo.tsinghua.edu.cn/~tigerchen/SubLoc.wsdl'
#wsdl='SubLoc.wsdl'
serv = WSDL.Proxy(wsdl)

#################### id_search
# by SWISSPROT ID
res = serv.id_search("SWISSPROT","O03978")
# get the number of matched entries
print len(res)
# get all entries' ID SQ LC CX DE OS
# SQ=sequence, LC=location, CX=cross database id, DE=description, OS=organism
for i in range(len(res)):
    print res[i].ID
    print res[i].SQ
    print res[i].DE
    print res[i].LC
    print res[i].OS
    print res[i].CX

# by DBSubLoc ID
res = serv.id_search("DBSubLoc","10043258")
# get the number of matched entries
print len(res)
# get all entries' ID SQ LC CX DE OS
# SQ=sequence, LC=location, CX=cross database id, DE=description, OS=organism
for i in range(len(res)):
    print res[i].ID
    print res[i].SQ
    print res[i].DE
    print res[i].LC
    print res[i].OS
    print res[i].CX

# by GO ID
# Caution! Search by GO ID may return many many entries, please be patient, thanks
res = serv.id_search("GO","0005739")
# get the number of matched entries
print len(res)
# get all entries' ID SQ LC CX DE OS
# SQ=sequence, LC=location, CX=cross database id, DE=description, OS=organism
for i in range(len(res)):
    print res[i].ID
    print res[i].SQ
    print res[i].DE
    print res[i].LC
    print res[i].OS
    print res[i].CX

############################ name_search
res=serv.name_search("p53")
# get the number of matched entries
print len(res)
# get all entries' ID SQ LC CX DE OS
# SQ=sequence, LC=location, CX=cross database id, DE=description, OS=organism
for i in range(len(res)):
    print res[i].ID
    print res[i].SQ
    print res[i].DE
    print res[i].LC
    print res[i].OS
    print res[i].CX

############################# blast_search
seq = "TKRFFNKNNRLNKGYAKTFSINEPDNNFYRKKFEHILPPVDLISEYESIYPGTLQELMHMAQKEQAHKHAIDLKNLKIQERIAKLTRICLLIFGIGLVVLIFLKLLK"
#seq = "TKRFFNKNNRLNKGY"
#res = serv.blast_search("all","full",seq,"1.0")
res = serv.blast_search("all","full",seq,"1")
# we provide two kinds of output formats: original BLAST output and parsed results by BioPerl's BPlite, users could choose one they like.
# get the original output of BLAST program, you could use BioPython to parse it quite easily. There are many example scripts on the Internet.
print res.plain
# or you can get the parsed result (using BioPerl's BPlite)
# the parsed output's fields, every field is separated by a TAB
#HIT_NUM    SCORE   BITS    PERCENT EXPECT  SUBJECT_NAME    IDENTITIES	MATCH_LENGTH	QUERY_START QUERY_END	SUBJECT_START	SUBJECT_END
print  res.parsed


###################################################################
############### SubLoc prediction by SVM
# for more details about the method, please see:
#Hua, S. and Sun, Z. (2001). Support vector machine approach for protein subcellular localization prediction. Bioinformatics 17, 721-8.
# for prokaryotic organisms 
seq = "TKRFFNKNNRLNKGYAKTFSINEPDNNFYRKKFEHILPPVDLISEYESIYPGTLQELMHMAQKEQAHKHAIDLKNLKIQERIAKLTRICLLIFGIGLVVLIFLKLLK"
pre = serv.pro_predict(seq)
# get predicted location
print pre.Prediction
print "\n"
# get expected accuracy
print pre.ExpectAcc
print "\n"
# get reliability index
print pre.RI
print "\n"

# for eukaryotic organisms
pre = serv.eu_predict(seq)
# get predicted location
print pre.Prediction
print "\n"
# get expected accuracy
print pre.ExpectAcc
print "\n"
# get reliability index
print pre.RI
print "\n"


######################################################################
################# SubLoc prediction by PSORT
# for more details about PSORT, please refer:
# Nakai, K. and Horton, P. (1999). PSORT: a program for detecting sorting signals in proteins and
# predicting their subcellular localization. Trends Biochem Sci 24, 34-6.
pre = serv.psort_predict(seq)
# get predicted location
print pre.Prediction;
print "\n";
# get all output information of PSORT
print pre.Detail
print "\n";

########################################################################
################## Submit new entries by users
ID="test"
DE="pseudo-entry for test"
OS="human"
LC="cytoplasmic"
CX="unknown"
SQ="XXXXXXXXXXXXXXXXXX"
feed = serv.feed_entry(ID,DE,OS,LC,CX,SQ)
print feed

## if you have a fasta file containing many sequences, you may use following code:
## need BioPython, if not installed, please visit www.biopython.org to download and install it.

#from Bio.SeqIO import FASTA
#import sys
#filename = '/your/path/to/fasta/file'
#handle = open(filename)
#it = FASTA.FastaReader(handle)
#seq = it.next()
#while seq:
#    print seq.name
#    print seq.seq
#    seq = it.next()
#handle.close()