def multiplealignment(self):
""" """
# get sequences & coordinated and rewrite Nodes to Organism identifiers
seqs,coords = self.get_maxsr_proteinsequences_and_coords()
coords = dict([ (self.organism_by_node(node),[min(vlist),max(vlist)+1]) for node,vlist in coords.iteritems() ])
seqs = dict([ (self.organism_by_node(node),seq) for node,seq in seqs.iteritems() ])
# align sequences with ClustalW
(alignedseqs,alignment) = clustalw( seqs= seqs )
# trim alignment for leading & trailing gaps
alignedseqs,alignment,coords = strip_alignment_for_exterior_gaps(alignedseqs,alignment,coords)
# return single string of multilined fasta
return "\n".join([">%s_orf_%s\n%s" % (k,self.node_by_organism(k)[1],v) for k,v in alignedseqs.iteritems()])
def multiplealignment(self):
""" """
# get sequences & coordinated and rewrite Nodes to Organism identifiers
seqs, coords = self.get_maxsr_proteinsequences_and_coords()
coords = dict([(self.organism_by_node(node),
[min(vlist), max(vlist) + 1])
for node, vlist in coords.iteritems()])
seqs = dict([(self.organism_by_node(node), seq)
for node, seq in seqs.iteritems()])
# align sequences with ClustalW
(alignedseqs, alignment) = clustalw(seqs=seqs)
# trim alignment for leading & trailing gaps
alignedseqs, alignment, coords = strip_alignment_for_exterior_gaps(
alignedseqs, alignment, coords)
# return single string of multilined fasta
return "\n".join([
">%s_orf_%s\n%s" % (k, self.node_by_organism(k)[1], v)
for k, v in alignedseqs.iteritems()
])
def _create_hmm_profile(cbg,
area="OMSR",
prevcbg=None,
nextcbg=None,
strip_nonaligned_residues=False,
verbose=False,
**kwargs):
"""
"""
# area must be one of
# OMSR MINSR MAXSR
# LEFTSPRDIF RIGTHSPRDIF
# OMSRANDLEFTSPRDIF OMSRANDRIGTHSPRDIF
# RIGTHORFEND
# update to default value
if not kwargs.has_key('sprdif_min_aa_length'):
kwargs['sprdif_min_aa_length'] = 20
if area == "OMSR":
if cbg.has_overall_minimal_spanning_range():
coords = cbg.overall_minimal_spanning_range()
else:
return None, {}
elif area == "MINSR":
if cbg.has_minimal_spanning_range():
coords = cbg.minimal_spanning_range()
else:
return None, {}
elif area == "MAXSR":
if cbg.has_maximal_spanning_range():
coords = cbg.maximal_spanning_range()
else:
return None, {}
elif area == "LEFTSPRDIF":
if cbg.has_left_spanningrange_difference(**kwargs):
coords = cbg.left_spanningrange_difference(**kwargs)
else:
return None, {}
elif area == "RIGTHSPRDIF":
if cbg.has_rigth_spanningrange_difference(**kwargs):
coords = cbg.rigth_spanningrange_difference(**kwargs)
else:
return None, {}
elif area == "OMSRANDLEFTSPRDIF":
kwargs['sprdif_min_aa_length'] = 20
if not cbg.has_overall_minimal_spanning_range() or\
not cbg.has_left_spanningrange_difference(**kwargs):
return None, {}
# if here, start preparing coords
coords = cbg.left_spanningrange_difference(**kwargs)
# remove short contributors to left SPRDIF
coords = _remove_short_sprdif_contributors(coords, verbose=verbose)
# increase coord range by OMSR area
omsr = cbg.overall_minimal_spanning_range()
for node, coordrange in coords.iteritems():
coords[node] = Set(range(min(coordrange), max(omsr[node]) + 1))
elif area == "OMSRANDRIGTHSPRDIF":
kwargs['sprdif_min_aa_length'] = 20
if not cbg.has_overall_minimal_spanning_range() or\
not cbg.has_rigth_spanningrange_difference(**kwargs):
return None, {}
# if here, start preparing coords
coords = cbg.rigth_spanningrange_difference(**kwargs)
# remove short contributors to left SPRDIF
coords = _remove_short_sprdif_contributors(coords, verbose=verbose)
# increase coord range by OMSR area
omsr = cbg.overall_minimal_spanning_range()
for node, coordrange in coords.iteritems():
coords[node] = Set(range(min(omsr[node]), max(coordrange) + 1))
elif area == "RIGTHORFEND":
# area in between MAXSR and orfend
if not cbg.has_maximal_spanning_range(): return None, {}
# get coords & obtain Orf ends
coords = cbg.maximal_spanning_range()
nodes = coords.keys()
for node in nodes:
organism = cbg.organism_by_node(node)
theorf = cbg.get_orfs_of_graph(organism=organism)[0]
coords[node] = range(max(coords[node]) + 1, theorf.protein_endPY)
# remove zero-length ranges
if len(coords[node]) == 0: del (coords[node])
else:
raise "WHAT ELSE!?"
############################################################################
if verbose:
print area, sum([(max(v) - min(v))
for k, v in coords.iteritems()]), len(coords)
############################################################################
# decrease coord range by prevcbg if applicable
if area in ["MAXSR", "LEFTSPRDIF", "OMSRANDLEFTSPRDIF"] and prevcbg:
omsr = prevcbg.overall_minimal_spanning_range()
for org in cbg.organism_set().intersection(prevcbg.organism_set()):
# omsr/coords have Node keys -> translate to Organism keys
nodeCbg = cbg.get_organism_nodes(org)[0]
nodePrev = prevcbg.get_organism_nodes(org)[0]
# check if node not deleted earlier in coords dict
if not coords.has_key(nodeCbg): continue
if not omsr.has_key(nodePrev): continue
sta = max([max(omsr[nodePrev]) + 1, min(coords[nodeCbg])])
end = max(coords[nodeCbg]) + 1
coords[nodeCbg] = Set(range(sta, end))
if not coords[nodeCbg]: del (coords[nodeCbg])
# decrease coord range by nextcbg if applicable
if area in ["MAXSR", "RIGTHSPRDIF", "OMSRANDRIGTHSPRDIF"] and nextcbg:
omsr = nextcbg.overall_minimal_spanning_range()
for org in cbg.organism_set().intersection(nextcbg.organism_set()):
# omsr/coords have Node keys -> translate to Organism keys
nodeCbg = cbg.get_organism_nodes(org)[0]
nodeNext = nextcbg.get_organism_nodes(org)[0]
# check if node not deleted earlier in coords dict
if not coords.has_key(nodeCbg): continue
if not omsr.has_key(nodeNext): continue
sta = min(coords[nodeCbg])
end = min([min(omsr[nodeNext]), max(coords[nodeCbg]) + 1])
coords[nodeCbg] = Set(range(sta, end))
if not coords[nodeCbg]: del (coords[nodeCbg])
# check if coords still present
if not coords: return None, {}
############################################################################
if verbose:
print area, sum([(max(v) - min(v))
for k, v in coords.iteritems()]), len(coords)
############################################################################
# do/redo _remove_short_sprdif_contributors id required
if area in [
"MAXSR", "LEFTSPRDIF", "RIGTHSPRDIF", "OMSRANDLEFTSPRDIF",
"OMSRANDRIGTHSPRDIF", "RIGTHORFEND"
]:
coords = _remove_short_sprdif_contributors(coords)
############################################################################
if verbose:
print area, sum([(max(v) - min(v))
for k, v in coords.iteritems()]), len(coords)
############################################################################
# check if at least 2 sequences/nodes are remaining
if len(coords) <= 1: return None, {}
# check sprdif_min_aa_length if applicable
if area in [
"RIGTHSPRDIF", "LEFTSPRDIF", "OMSRANDRIGTHSPRDIF",
"OMSRANDLEFTSPRDIF"
]:
maxlength = max([len(vlist) for vlist in coords.values()])
if maxlength < kwargs['sprdif_min_aa_length']:
return None, {}
# if here, obtain sequences and build HMM search profile
# get fasta sequences and
fastaseqs = cbg._get_sequences_by_coords(coords)
# rewrite dict (node) keys to string keys
fastaseqs, coords = _rename_dict_keys_to_strings(fastaseqs, coords)
# remove empty sequence strings from fastaseqs dict
empty_seq_keys = []
for k, seq in fastaseqs.iteritems():
if seq == "" or len(seq) == 1:
empty_seq_keys.append(k)
for k in empty_seq_keys:
del (coords[k])
del (fastaseqs[k])
# check (again) if at least 2 sequences/nodes are remaining
if len(coords) <= 1: return None, {}
# rewrite coords to (min,max) tuple
coords = dict([(key, [min(vlist), max(vlist) + 1])
for key, vlist in coords.iteritems()])
# perform clustalw multiple alignment
(alignedseqs, alignment) = clustalw(seqs=fastaseqs)
# strip exterior gaps in case of OMSR/MINSR area
if area in ["OMSR", "MINSR"]:
alignedseqs, alignment, coords = strip_alignment_for_exterior_gaps(
deepcopy(alignedseqs), deepcopy(alignment), deepcopy(coords))
# strip poorly conserved residues in case of RIGTHORFEND
if area in ["RIGTHORFEND"]:
alignedseqs, alignment, coords = strip_poorly_supported_tails(
deepcopy(alignedseqs), deepcopy(alignment), deepcopy(coords), 0.20)
# strip_overall_nonaligned_residues if requested for: THIS IS VERY RIGID!
if strip_nonaligned_residues:
alignedseqs, alignment, coords = strip_overall_nonaligned_residues(
deepcopy(alignedseqs), deepcopy(alignment), deepcopy(coords))
# check if alignment was completely consumed or not
if not alignment or len(alignment) <= 1:
return None, {}
############################################################################
if verbose:
print "## HMM clustalw input profile:", prevcbg != None, area, nextcbg != None
for node, algseq in alignedseqs.iteritems():
print algseq, node, coords[node]
print alignment
############################################################################
# make unique filename for hmm profile file
fname_hmm_profile = "hmmbuild_profile_%s.hmmprof" % get_random_string_tag()
# write multiple alignment input file
writeMultiFasta(alignedseqs, fname_hmm_profile)
# make hmmbuild file of the multiplealignment
fname_hmmbuild_file = hmmbuild_protein(fname_hmm_profile)
# remove hmm profile multiple alignment file
osRemove(fname_hmm_profile)
# return HMM serach profile filename
return fname_hmmbuild_file, coords
def hmmhit2pacbp(queryorf,
queryorg,
querycoords,
sbjctorf,
sbjctorg,
hmmhit,
verbose=False):
"""
"""
# trim hmmhit for unmatched characters
(sbjct_header, sbjct_start, sbjct_end, query_start, query_end, query,
match, sbjct, score, expect) = hmmhit
while match and match[0] == ' ':
query = query[1:]
match = match[1:]
sbjct = sbjct[1:]
sbjct_start += 1
query_start += 1
while match and match[-1] == ' ':
query = query[0:-1]
match = match[0:-1]
sbjct = sbjct[0:-1]
sbjct_end -= 1
query_end -= 1
# get orf, node and AA and DNA coordinates of this sbjct hit;
# correct for -1 offset in start coordinate!!
sbjct_aa_start = sbjct_start - 1 + sbjctorf.protein_startPY
sbjct_aa_end = sbjct_end + sbjctorf.protein_startPY
sbjctNode = (sbjctorg, sbjctorf.id)
query = query.replace(".", "-").upper()
sbjct = sbjct.replace(".", "-").upper()
############################################################################
if verbose:
print "hmmhit2pacbp CREATING pacbps for organism/orf: (%s,%s)" % (
sbjctorg, sbjctorf.id)
print "hmmhit2pacbp Q '%s'" % query
print "hmmhit2pacbp m '%s'" % match
print "hmmhit2pacbp S '%s'" % sbjct
print "hmmQ:", query, query_start, query_end, "gaps:",
print query.count('-'), len(query)
print "hmmM:", match
print "hmmS:", sbjct, sbjctNode, sbjct_aa_start, sbjct_aa_end,
print "len:", sbjct_aa_end - sbjct_aa_start, len(sbjct)
############################################################################
# get Node and sequence of the query
queryNode = (queryorg, queryorf.id)
queryseq = deepcopy(query)
# calculate query sequence position on queryorf
query_aa_start = querycoords[0] + query_start - 1
query_aa_end = query_aa_start + len(queryseq) - queryseq.count('-')
############################################################################
if verbose:
print "hmmq:", queryseq, queryNode, query_aa_start, query_aa_end,
print "len:", query_aa_end - query_aa_start, len(queryseq)
############################################################################
# make a deepcopy; sbjct is needed unchanged for the next iteration
# in the for loop, but here we want to trim of gap sequences
sbjctseq = deepcopy(sbjct)
sbjctaastart = deepcopy(sbjct_aa_start)
sbjctaaend = deepcopy(sbjct_aa_end)
while queryseq and queryseq[0] == '-':
queryseq = queryseq[1:]
sbjctseq = sbjctseq[1:]
sbjctaastart += 1
while sbjctseq and sbjctseq[0] == '-':
queryseq = queryseq[1:]
sbjctseq = sbjctseq[1:]
query_aa_start += 1
while queryseq and queryseq[-1] == '-':
queryseq = queryseq[0:-1]
sbjctseq = sbjctseq[0:-1]
sbjctaaend -= 1
while sbjctseq and sbjctseq[-1] == '-':
queryseq = queryseq[0:-1]
sbjctseq = sbjctseq[0:-1]
query_aa_end -= 1
# NEW NEW code in december 2010. Since inwpCBGs are implemented, HMM
# profiles are build from clustalw alignments which have loosely aligned
# tails (SPRDIF sequences). Problem with HMM is, that in the result file
# no information is written on where in teh constructed HMM this hit
# starts. This **sucks** because special care was taken in ABFGP code to
# make shure the exact aa-coordinates of the applied sequences to ClustalW
# are known. Hmmbuild here nullifies this effort by not giving start
# coordinates. Therefore, we have to check the exact start position
# of the HMM match on the queryorf.
if queryseq.replace("-", "") != queryorf.getaas(query_aa_start,
query_aa_end):
# obtain (search) query sequence, replace gaps by X symbol
searchqueryseq = queryseq.upper().replace("-", "X")
# count length of the query sequence; here IGNORE THE GAPS!!
seqlen = len(queryseq.upper().replace("-", ""))
# make fasta sequence dictionary
seqdict = {
'query_hmm': searchqueryseq,
'query_orf': queryorf.protein_sequence,
}
# make coords dictionary for remapping
coords = {
'query_hmm': [0, seqlen],
'query_orf': [queryorf.protein_startPY, queryorf.protein_endPY],
}
# perform clustalw multiple alignment
(alignedseqs, alignment) = clustalw(seqs=seqdict)
# strip exterior gaps
alignedseqs, alignment, coords = strip_alignment_for_exterior_gaps(
deepcopy(alignedseqs), deepcopy(alignment), deepcopy(coords))
if alignedseqs['query_hmm'].count("-") > 0:
# in (very) exceptional cases, gaps can be introduced in the
# clustalw alignment in the HMM seq. This normally does not
# occur! Fix this here by placing gaps in sbjctseq too.
sbjctseq_as_list = list(sbjctseq)
for pos in range(0, len(alignedseqs['query_hmm'])):
if alignedseqs['query_hmm'][pos] == "-":
sbjctseq_as_list.insert(pos, "-")
if alignedseqs['query_hmm'].find("-", pos) == -1:
break
sbjctseq = "".join(sbjctseq_as_list)
########################################################################
if verbose:
print "\t", "FALSE::", sbjctseq, "[ WITH GAPS,SBJCT ]"
print "\t", "FALSE::", queryseq, "[ WITH GAPS ]"
for k, algseq in alignedseqs.iteritems():
print "\t", "FALSE::", algseq, k, coords[k], len(algseq)
print "\t", "FALSE::", sbjctseq, "SBJCT", len(sbjctseq)
print "\t", "FALSE::", alignment, "ALMNT", len(alignment)
print "\t", "SOLVED:", len(
alignedseqs['query_orf']) == len(sbjctseq)
########################################################################
# update query sequence & coordinates
if len(alignedseqs['query_orf']) == len(sbjctseq):
queryseq = alignedseqs['query_orf']
query_aa_start = coords['query_orf'][0]
query_aa_end = coords['query_orf'][1]
else:
# still not identical lengths. ClustalW recovery of HMM hit
# failed miserably. For now: omit
# TODO: resolve this case!!
# example: --filewithloci examples/bilal/CFU_830450.bothss.csv
# ## HMM clustalw input profile: False MAXSR True
# FPKGCESGKFINWKTFKANGVNLGAWLAKEKTHDPVW foxga [561, 598]
# FQRACR--KFID-ETLSAHAL---EWESKEIVPPEVW CFU [357, 388]
# hmmhit2pacbp CREATING pacbps for organism/orf: (NP1064101[anid],1)
# hmmhit2pacbp Q 'FQKACRSGKFIDWKTLKANALNLGEWLAKEKVHD'
# hmmhit2pacbp m '+ ka + F W k + nLG Wl E d'
# hmmhit2pacbp S 'YTKAFQ--PF-SWSSAKVRGANLGGWLVQEASID'
# hmmQ: FQKACRSGKFIDWKTLKANALNLGEWLAKEKVHD 1 34 gaps: 0 34
# hmmM: + ka + F W k + nLG Wl E d
# hmmS: YTKAFQ--PF-SWSSAKVRGANLGGWLVQEASID ('NP1064101[anid]', 1) 33 64 len: 31 34
# hmmq: FQKACRSGKFIDWKTLKANALNLGEWLAKEKVHD ('CFU', 91) 357 391 len: 34 34
# FALSE:: YTKAFQ---------PF-SWSS-----------------AKVR----------GANLGG--W-LVQEASID [ WITH GAPS,SBJCT ]
# FALSE:: FQKACRSGKFIDWKTLKANALNLGEWLAKEKVHD [ WITH GAPS ]
# FALSE:: FQKACR-------SGKFIDWKT-----------------LKAN----------ALNLGE--W-LAKEKVH query_hmm [0, 33] 70
# FALSE:: FQRACRKFIDETLSAHALEWESKEIVPPEVWQRFAEANMLIPNLAALASRMVGEIGIGNAFWRLSVQGLR query_orf [357, 427] 70
# FALSE:: YTKAFQ---------PF-SWSS-----------------AKVR----------GANLGG--W-LVQEASID SBJCT 71
# FALSE:: **:*** *.: ::*:: * .* :.:*: * *: : :: ALMNT 70
# SOLVED: False
# Pacbp creation failed!
return False, None
if queryseq and sbjctseq:
################################################################
if len(queryseq) != len(sbjctseq):
# this will result in a exception to be raised:
# pacb.exceptions.InproperlyAppliedArgument
# print data here about what went wrong, then
# just let the error be raised
print queryseq, len(queryseq), sbjctseq, len(sbjctseq)
print hmmhit
print "Q:", query_aa_start, query_aa_end,
print query_aa_end - query_aa_start, "len:", len(queryseq)
print "S:", sbjctaastart, sbjctaaend,
print sbjctaaend - sbjctaastart, "len:", len(sbjctseq)
################################################################
pacbpinput = (queryseq, sbjctseq, query_aa_start, sbjctaastart)
pacbp = PacbP(input=pacbpinput)
# remove consistent internal gaps caused hy HMM profile search
pacbp.strip_consistent_internal_gaps()
pacbp.source = 'hmmsearch'
pacbporf = PacbPORF(pacbp, queryorf, sbjctorf)
pacbporf.strip_unmatched_ends()
if pacbporf.length == 0:
# Pacbp creation failed!
return False, None
else:
pacbporf.extend_pacbporf_after_stops()
pacbpkey = pacbporf.construct_unique_key(queryNode, sbjctNode)
# return unique key and pacbporf
return (pacbpkey, queryNode, sbjctNode), pacbporf
else:
# Pacbp creation failed!
return False, None
def _create_hmm_profile(cbg,area="OMSR",prevcbg=None,nextcbg=None,
strip_nonaligned_residues=False,
verbose=False,**kwargs):
"""
"""
# area must be one of
# OMSR MINSR MAXSR
# LEFTSPRDIF RIGTHSPRDIF
# OMSRANDLEFTSPRDIF OMSRANDRIGTHSPRDIF
# RIGTHORFEND
# update to default value
if not kwargs.has_key('sprdif_min_aa_length'):
kwargs['sprdif_min_aa_length'] = 20
if area == "OMSR":
if cbg.has_overall_minimal_spanning_range():
coords = cbg.overall_minimal_spanning_range()
else:
return None, {}
elif area == "MINSR":
if cbg.has_minimal_spanning_range():
coords = cbg.minimal_spanning_range()
else:
return None, {}
elif area == "MAXSR":
if cbg.has_maximal_spanning_range():
coords = cbg.maximal_spanning_range()
else:
return None, {}
elif area == "LEFTSPRDIF":
if cbg.has_left_spanningrange_difference(**kwargs):
coords = cbg.left_spanningrange_difference(**kwargs)
else:
return None, {}
elif area == "RIGTHSPRDIF":
if cbg.has_rigth_spanningrange_difference(**kwargs):
coords = cbg.rigth_spanningrange_difference(**kwargs)
else:
return None, {}
elif area == "OMSRANDLEFTSPRDIF":
kwargs['sprdif_min_aa_length'] = 20
if not cbg.has_overall_minimal_spanning_range() or\
not cbg.has_left_spanningrange_difference(**kwargs):
return None, {}
# if here, start preparing coords
coords = cbg.left_spanningrange_difference(**kwargs)
# remove short contributors to left SPRDIF
coords = _remove_short_sprdif_contributors(coords,verbose=verbose)
# increase coord range by OMSR area
omsr = cbg.overall_minimal_spanning_range()
for node,coordrange in coords.iteritems():
coords[node] = Set( range( min(coordrange), max(omsr[node])+1 ) )
elif area == "OMSRANDRIGTHSPRDIF":
kwargs['sprdif_min_aa_length'] = 20
if not cbg.has_overall_minimal_spanning_range() or\
not cbg.has_rigth_spanningrange_difference(**kwargs):
return None, {}
# if here, start preparing coords
coords = cbg.rigth_spanningrange_difference(**kwargs)
# remove short contributors to left SPRDIF
coords = _remove_short_sprdif_contributors(coords,verbose=verbose)
# increase coord range by OMSR area
omsr = cbg.overall_minimal_spanning_range()
for node,coordrange in coords.iteritems():
coords[node] = Set( range( min(omsr[node]), max(coordrange)+1 ) )
elif area == "RIGTHORFEND":
# area in between MAXSR and orfend
if not cbg.has_maximal_spanning_range(): return None, {}
# get coords & obtain Orf ends
coords = cbg.maximal_spanning_range()
nodes = coords.keys()
for node in nodes:
organism = cbg.organism_by_node(node)
theorf = cbg.get_orfs_of_graph(organism=organism)[0]
coords[node] = range(max(coords[node])+1,theorf.protein_endPY)
# remove zero-length ranges
if len(coords[node]) == 0: del(coords[node])
else:
raise "WHAT ELSE!?"
############################################################################
if verbose: print area, sum([(max(v)-min(v)) for k,v in coords.iteritems()]),len(coords)
############################################################################
# decrease coord range by prevcbg if applicable
if area in ["MAXSR","LEFTSPRDIF","OMSRANDLEFTSPRDIF"] and prevcbg:
omsr = prevcbg.overall_minimal_spanning_range()
for org in cbg.organism_set().intersection( prevcbg.organism_set() ):
# omsr/coords have Node keys -> translate to Organism keys
nodeCbg = cbg.get_organism_nodes(org)[0]
nodePrev = prevcbg.get_organism_nodes(org)[0]
# check if node not deleted earlier in coords dict
if not coords.has_key(nodeCbg): continue
if not omsr.has_key(nodePrev): continue
sta = max( [ max(omsr[nodePrev])+1, min(coords[nodeCbg]) ] )
end = max(coords[nodeCbg])+1
coords[nodeCbg] = Set(range(sta,end))
if not coords[nodeCbg]: del( coords[nodeCbg] )
# decrease coord range by nextcbg if applicable
if area in ["MAXSR","RIGTHSPRDIF","OMSRANDRIGTHSPRDIF"] and nextcbg:
omsr = nextcbg.overall_minimal_spanning_range()
for org in cbg.organism_set().intersection( nextcbg.organism_set() ):
# omsr/coords have Node keys -> translate to Organism keys
nodeCbg = cbg.get_organism_nodes(org)[0]
nodeNext = nextcbg.get_organism_nodes(org)[0]
# check if node not deleted earlier in coords dict
if not coords.has_key(nodeCbg): continue
if not omsr.has_key(nodeNext): continue
sta = min(coords[nodeCbg])
end = min( [ min(omsr[nodeNext]), max(coords[nodeCbg])+1 ] )
coords[nodeCbg] = Set(range(sta,end))
if not coords[nodeCbg]: del( coords[nodeCbg] )
# check if coords still present
if not coords: return None, {}
############################################################################
if verbose: print area, sum([(max(v)-min(v)) for k,v in coords.iteritems()]),len(coords)
############################################################################
# do/redo _remove_short_sprdif_contributors id required
if area in ["MAXSR","LEFTSPRDIF","RIGTHSPRDIF",
"OMSRANDLEFTSPRDIF","OMSRANDRIGTHSPRDIF","RIGTHORFEND"]:
coords = _remove_short_sprdif_contributors(coords)
############################################################################
if verbose: print area, sum([(max(v)-min(v)) for k,v in coords.iteritems()]),len(coords)
############################################################################
# check if at least 2 sequences/nodes are remaining
if len(coords) <= 1: return None, {}
# check sprdif_min_aa_length if applicable
if area in ["RIGTHSPRDIF","LEFTSPRDIF","OMSRANDRIGTHSPRDIF",
"OMSRANDLEFTSPRDIF"]:
maxlength = max([ len(vlist) for vlist in coords.values() ])
if maxlength < kwargs['sprdif_min_aa_length']:
return None, {}
# if here, obtain sequences and build HMM search profile
# get fasta sequences and
fastaseqs = cbg._get_sequences_by_coords(coords)
# rewrite dict (node) keys to string keys
fastaseqs, coords = _rename_dict_keys_to_strings(fastaseqs, coords)
# remove empty sequence strings from fastaseqs dict
empty_seq_keys = []
for k,seq in fastaseqs.iteritems():
if seq == "" or len(seq) == 1:
empty_seq_keys.append(k)
for k in empty_seq_keys:
del(coords[k])
del(fastaseqs[k])
# check (again) if at least 2 sequences/nodes are remaining
if len(coords) <= 1: return None, {}
# rewrite coords to (min,max) tuple
coords = dict([ (key,[min(vlist),max(vlist)+1]) for key,vlist in coords.iteritems() ])
# perform clustalw multiple alignment
(alignedseqs,alignment) = clustalw( seqs= fastaseqs )
# strip exterior gaps in case of OMSR/MINSR area
if area in ["OMSR","MINSR"]:
alignedseqs,alignment,coords = strip_alignment_for_exterior_gaps(
deepcopy(alignedseqs),deepcopy(alignment),deepcopy(coords) )
# strip poorly conserved residues in case of RIGTHORFEND
if area in ["RIGTHORFEND"]:
alignedseqs,alignment,coords = strip_poorly_supported_tails(
deepcopy(alignedseqs),deepcopy(alignment),deepcopy(coords),0.20 )
# strip_overall_nonaligned_residues if requested for: THIS IS VERY RIGID!
if strip_nonaligned_residues:
alignedseqs,alignment,coords = strip_overall_nonaligned_residues(
deepcopy(alignedseqs),deepcopy(alignment),deepcopy(coords) )
# check if alignment was completely consumed or not
if not alignment or len(alignment) <= 1:
return None, {}
############################################################################
if verbose:
print "## HMM clustalw input profile:",prevcbg!=None,area,nextcbg!=None
for node,algseq in alignedseqs.iteritems():
print algseq, node, coords[node]
print alignment
############################################################################
# make unique filename for hmm profile file
fname_hmm_profile = "hmmbuild_profile_%s.hmmprof" % get_random_string_tag()
# write multiple alignment input file
writeMultiFasta(alignedseqs,fname_hmm_profile)
# make hmmbuild file of the multiplealignment
fname_hmmbuild_file = hmmbuild_protein( fname_hmm_profile )
# remove hmm profile multiple alignment file
osRemove(fname_hmm_profile)
# return HMM serach profile filename
return fname_hmmbuild_file, coords
def hmmhit2pacbp(queryorf,queryorg,querycoords,sbjctorf,sbjctorg,hmmhit,verbose=False):
"""
"""
# trim hmmhit for unmatched characters
( sbjct_header, sbjct_start, sbjct_end,
query_start, query_end,
query, match, sbjct, score, expect ) = hmmhit
while match and match[0] == ' ':
query = query[1:]
match = match[1:]
sbjct = sbjct[1:]
sbjct_start+=1
query_start+=1
while match and match[-1] == ' ':
query = query[0:-1]
match = match[0:-1]
sbjct = sbjct[0:-1]
sbjct_end-=1
query_end-=1
# get orf, node and AA and DNA coordinates of this sbjct hit;
# correct for -1 offset in start coordinate!!
sbjct_aa_start = sbjct_start - 1 + sbjctorf.protein_startPY
sbjct_aa_end = sbjct_end + sbjctorf.protein_startPY
sbjctNode = (sbjctorg,sbjctorf.id)
query = query.replace(".","-").upper()
sbjct = sbjct.replace(".","-").upper()
############################################################################
if verbose:
print "hmmhit2pacbp CREATING pacbps for organism/orf: (%s,%s)" % (
sbjctorg,sbjctorf.id)
print "hmmhit2pacbp Q '%s'" % query
print "hmmhit2pacbp m '%s'" % match
print "hmmhit2pacbp S '%s'" % sbjct
print "hmmQ:", query, query_start, query_end, "gaps:",
print query.count('-'), len(query)
print "hmmM:", match
print "hmmS:", sbjct, sbjctNode, sbjct_aa_start, sbjct_aa_end,
print "len:", sbjct_aa_end-sbjct_aa_start , len(sbjct)
############################################################################
# get Node and sequence of the query
queryNode = (queryorg,queryorf.id)
queryseq = deepcopy(query)
# calculate query sequence position on queryorf
query_aa_start = querycoords[0] + query_start - 1
query_aa_end = query_aa_start + len(queryseq) - queryseq.count('-')
############################################################################
if verbose:
print "hmmq:", queryseq, queryNode, query_aa_start, query_aa_end,
print "len:", query_aa_end-query_aa_start, len(queryseq)
############################################################################
# make a deepcopy; sbjct is needed unchanged for the next iteration
# in the for loop, but here we want to trim of gap sequences
sbjctseq = deepcopy(sbjct)
sbjctaastart = deepcopy(sbjct_aa_start)
sbjctaaend = deepcopy(sbjct_aa_end)
while queryseq and queryseq[0] == '-':
queryseq = queryseq[1:]
sbjctseq = sbjctseq[1:]
sbjctaastart+=1
while sbjctseq and sbjctseq[0] == '-':
queryseq = queryseq[1:]
sbjctseq = sbjctseq[1:]
query_aa_start+=1
while queryseq and queryseq[-1] == '-':
queryseq = queryseq[0:-1]
sbjctseq = sbjctseq[0:-1]
sbjctaaend-=1
while sbjctseq and sbjctseq[-1] == '-':
queryseq = queryseq[0:-1]
sbjctseq = sbjctseq[0:-1]
query_aa_end-=1
# NEW NEW code in december 2010. Since inwpCBGs are implemented, HMM
# profiles are build from clustalw alignments which have loosely aligned
# tails (SPRDIF sequences). Problem with HMM is, that in the result file
# no information is written on where in teh constructed HMM this hit
# starts. This **sucks** because special care was taken in ABFGP code to
# make shure the exact aa-coordinates of the applied sequences to ClustalW
# are known. Hmmbuild here nullifies this effort by not giving start
# coordinates. Therefore, we have to check the exact start position
# of the HMM match on the queryorf.
if queryseq.replace("-","") != queryorf.getaas(query_aa_start,query_aa_end):
# obtain (search) query sequence, replace gaps by X symbol
searchqueryseq = queryseq.upper().replace("-","X")
# count length of the query sequence; here IGNORE THE GAPS!!
seqlen = len(queryseq.upper().replace("-",""))
# make fasta sequence dictionary
seqdict = {
'query_hmm': searchqueryseq,
'query_orf': queryorf.protein_sequence,
}
# make coords dictionary for remapping
coords = {
'query_hmm':[0,seqlen],
'query_orf':[queryorf.protein_startPY,queryorf.protein_endPY],
}
# perform clustalw multiple alignment
(alignedseqs,alignment) = clustalw( seqs= seqdict )
# strip exterior gaps
alignedseqs,alignment,coords = strip_alignment_for_exterior_gaps(
deepcopy(alignedseqs),deepcopy(alignment),deepcopy(coords) )
if alignedseqs['query_hmm'].count("-") > 0:
# in (very) exceptional cases, gaps can be introduced in the
# clustalw alignment in the HMM seq. This normally does not
# occur! Fix this here by placing gaps in sbjctseq too.
sbjctseq_as_list = list(sbjctseq)
for pos in range(0,len(alignedseqs['query_hmm'])):
if alignedseqs['query_hmm'][pos] == "-":
sbjctseq_as_list.insert(pos,"-")
if alignedseqs['query_hmm'].find("-",pos) == -1:
break
sbjctseq = "".join(sbjctseq_as_list)
########################################################################
if verbose:
print "\t", "FALSE::", sbjctseq, "[ WITH GAPS,SBJCT ]"
print "\t", "FALSE::", queryseq, "[ WITH GAPS ]"
for k,algseq in alignedseqs.iteritems():
print "\t", "FALSE::", algseq, k, coords[k], len(algseq)
print "\t", "FALSE::", sbjctseq, "SBJCT", len(sbjctseq)
print "\t", "FALSE::", alignment, "ALMNT", len(alignment)
print "\t", "SOLVED:", len(alignedseqs['query_orf']) == len(sbjctseq)
########################################################################
# update query sequence & coordinates
if len(alignedseqs['query_orf']) == len(sbjctseq):
queryseq = alignedseqs['query_orf']
query_aa_start = coords['query_orf'][0]
query_aa_end = coords['query_orf'][1]
else:
# still not identical lengths. ClustalW recovery of HMM hit
# failed miserably. For now: omit
# TODO: resolve this case!!
# example: --filewithloci examples/bilal/CFU_830450.bothss.csv
# ## HMM clustalw input profile: False MAXSR True
# FPKGCESGKFINWKTFKANGVNLGAWLAKEKTHDPVW foxga [561, 598]
# FQRACR--KFID-ETLSAHAL---EWESKEIVPPEVW CFU [357, 388]
# hmmhit2pacbp CREATING pacbps for organism/orf: (NP1064101[anid],1)
# hmmhit2pacbp Q 'FQKACRSGKFIDWKTLKANALNLGEWLAKEKVHD'
# hmmhit2pacbp m '+ ka + F W k + nLG Wl E d'
# hmmhit2pacbp S 'YTKAFQ--PF-SWSSAKVRGANLGGWLVQEASID'
# hmmQ: FQKACRSGKFIDWKTLKANALNLGEWLAKEKVHD 1 34 gaps: 0 34
# hmmM: + ka + F W k + nLG Wl E d
# hmmS: YTKAFQ--PF-SWSSAKVRGANLGGWLVQEASID ('NP1064101[anid]', 1) 33 64 len: 31 34
# hmmq: FQKACRSGKFIDWKTLKANALNLGEWLAKEKVHD ('CFU', 91) 357 391 len: 34 34
# FALSE:: YTKAFQ---------PF-SWSS-----------------AKVR----------GANLGG--W-LVQEASID [ WITH GAPS,SBJCT ]
# FALSE:: FQKACRSGKFIDWKTLKANALNLGEWLAKEKVHD [ WITH GAPS ]
# FALSE:: FQKACR-------SGKFIDWKT-----------------LKAN----------ALNLGE--W-LAKEKVH query_hmm [0, 33] 70
# FALSE:: FQRACRKFIDETLSAHALEWESKEIVPPEVWQRFAEANMLIPNLAALASRMVGEIGIGNAFWRLSVQGLR query_orf [357, 427] 70
# FALSE:: YTKAFQ---------PF-SWSS-----------------AKVR----------GANLGG--W-LVQEASID SBJCT 71
# FALSE:: **:*** *.: ::*:: * .* :.:*: * *: : :: ALMNT 70
# SOLVED: False
# Pacbp creation failed!
return False, None
if queryseq and sbjctseq:
################################################################
if len(queryseq) != len(sbjctseq):
# this will result in a exception to be raised:
# pacb.exceptions.InproperlyAppliedArgument
# print data here about what went wrong, then
# just let the error be raised
print queryseq, len(queryseq), sbjctseq, len(sbjctseq)
print hmmhit
print "Q:", query_aa_start, query_aa_end,
print query_aa_end - query_aa_start, "len:", len(queryseq)
print "S:", sbjctaastart, sbjctaaend,
print sbjctaaend - sbjctaastart, "len:",len(sbjctseq)
################################################################
pacbpinput = (queryseq,sbjctseq,query_aa_start,sbjctaastart)
pacbp = PacbP(input=pacbpinput)
# remove consistent internal gaps caused hy HMM profile search
pacbp.strip_consistent_internal_gaps()
pacbp.source = 'hmmsearch'
pacbporf = PacbPORF(pacbp,queryorf,sbjctorf)
pacbporf.strip_unmatched_ends()
if pacbporf.length==0:
# Pacbp creation failed!
return False, None
else:
pacbporf.extend_pacbporf_after_stops()
pacbpkey = pacbporf.construct_unique_key(queryNode,sbjctNode)
# return unique key and pacbporf
return (pacbpkey,queryNode,sbjctNode), pacbporf
else:
# Pacbp creation failed!
return False, None
