def get_reverse_cbg(cbg,frame,verbose=False):
"""
Get the ReversecomplementCodingBlockGraph in requested frame of this CBG
@type cbg: CodingBlockGraph
@param cbg: CodingBlockGraph to reversecomplement
@type frame: integer
@param frame: 0,1 or 2
@type verbose: Boolean
@param verbose: print intermediate info to STDOUT for debugging purposes
@rtype: ReversecomplementCodingBlockGraph or None
@return: ReversecomplementCodingBlockGraph (when existing) or None
"""
min_orf_length = (cbg.omsrlength()/2)*3
orfs = get_reverse_strand_orfsets(cbg,frame,min_orf_length=min_orf_length)
# remap the identifiers of the orf objects i.o.t....
multifastas = {}
blastdbs = {}
pacbpcol = PacbpCollectionGraph()
dpcpacbpcol = PacbpCollectionGraph() # ``deepcopied`` variant for pacbps
for org in orfs.keys():
fname = "%s_reversecbg_%s.mfa" % (org,cbg.barcode())
writeMultiFasta(orfs[org].tofastadict(),fname)
multifastas[org] = fname
########################################################################
if verbose:
print "ORFS:", org, len(orfs[org].orfs),
print [len(o.protein_sequence) for o in orfs[org].orfs ]
########################################################################
revpacbps = {}
for orgQ,orgS in cbg.pairwisecrosscombinations_organism():
# create blastdb if it does not exist yet
if not blastdbs.has_key(orgS):
formatdb(fname=multifastas[orgS])
blastdbs[orgS] = multifastas[orgS]
revpacbporfs = {}
for orfQ in orfs[orgQ].orfs:
# run blast_seqs2db
blastrec = blastall_seq2db(orfQ.id,orfQ.protein_sequence,
dbname="./"+blastdbs[orgS])
if len(blastrec.alignments) == 0: continue
for alignment in blastrec.alignments:
# obtain coordinates from sbjct orf identifier
orfS = orfs[orgS].get_orf_by_id(alignment.title.replace(">",""))
# take only the *best* HSP (highest scoring first one)
hsp = alignment.hsps[0]
# skip if hsp is very short
if len(hsp.query) < cbg.omsrlength()/2: continue
# correct to absolute positions
hsp.query_start = hsp.query_start + orfQ.protein_startPY
hsp.sbjct_start = hsp.sbjct_start + orfS.protein_startPY
# initialize the PacbP
pacbporf = pacb.conversion.pacbp2pacbporf(
pacb.PacbP(blastp_hsp=hsp),orfQ,orfS)
################################################################
if verbose:
print pacbporf, orgQ,orgS, orfQ
print pacbporf.query
print pacbporf.match
print pacbporf.sbjct
###pacbporf.print_protein_and_dna()
################################################################
nodeQ = ( orgQ, orfQ.protein_startPY )
nodeS = ( orgS, orfS.protein_startPY )
uqkey = pacbporf.construct_unique_key(nodeQ,nodeS)
if not nodeQ in pacbpcol.get_nodes(): pacbpcol.add_node(nodeQ)
if not nodeS in pacbpcol.get_nodes(): pacbpcol.add_node(nodeS)
pacbpcol.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
# store to dpcpacbpcol -> pacbpcol is broken in pieces lateron!
dpcpacbpcol.pacbps[(uqkey,nodeQ,nodeS)] = pacbporf
# file cleanup
_file_cleanup(multifastas.values())
_file_cleanup(["formatdb.log"])
_file_cleanup([ fname+".*" for fname in blastdbs.values()])
if not pacbpcol.organism_set_size() == cbg.organism_set_size():
# no CBG on the reverse strand
return None
# ``deepcopy`` PacbPcollection
dpcpacbpcol.add_nodes( pacbpcol.get_nodes() )
for (uqkey,nodeQ,nodeS) in dpcpacbpcol.pacbps.keys():
(bitscore,length,orfQid,orfSid) = uqkey
dpcpacbpcol.add_edge(nodeQ,nodeS,wt=bitscore)
############################################################################
if verbose:
print pacbpcol, "bitscores:",
print [ pacbporf.bitscore for pacbporf in dpcpacbpcol.pacbps.values() ]
############################################################################
# do some transformations on the pacbpcol
pacbpcol.remove_low_connectivity_nodes(min_connectivity=cbg.node_count()-1)
splittedCBGs = pacbpcol.find_fully_connected_subgraphs(
edges=cbg.node_count()-1 , max_missing_edges=0 )
# convert to list of CBGs and do some transformations
cbgList = ListOfCodingBlockGraphs(splittedCBGs,input={},crossdata={})
cbgList.remove_all_but_complete_cbgs()
cbgList.harvest_pacbps_from_pacbpcollection(dpcpacbpcol)
cbgList.remove_cbgs_without_omsr()
cbgList.update_edge_weights_by_minimal_spanning_range()
cbgList.order_list_by_attribute(order_by='total_weight',reversed=True)
############################################################################
if verbose:
for revcbg in cbgList:
print "revCBG:", revcbg
############################################################################
if not cbgList:
# no CBG on the reverse strand
return None
else:
# return the highest scoring CBG as a ReversecomlementCodingBlockGraph
return CodingBlockGraph2ReversecomlementCodingBlockGraph(
cbgList.codingblockgraphs[0])
def detect_and_remove_single_nonfinal_inwpcbg(inwpcbgs,PCG,GENE_IDENTIFIER_SET,
verbose=False):
"""
Allow deletion of a very shitty, single inwpCBG from the end of the list
"""
# we need at least 2 inwpCBGs in order to remove one of them
if len(inwpcbgs) <= 1: return False
lastInwpCBG = inwpcbgs[-1]
prevInwpCBG = inwpcbgs[-2]
lastNodeList = [ lastInwpCBG.get_organism_nodes(org)[0] for org in\
lastInwpCBG.organism_set().intersection(GENE_IDENTIFIER_SET) ]
prevNodeList = [ prevInwpCBG.get_organism_nodes(org)[0] for org in\
prevInwpCBG.organism_set().intersection(GENE_IDENTIFIER_SET) ]
# identical nodes -> do not delete. Only go for very obvious things
if Set(lastNodeList).intersection(prevNodeList): return False
ntdistdict = prevInwpCBG.nt_spacing_between_codingblocks([lastInwpCBG])
tcodedistdict = prevInwpCBG.tcode_spacing_between_codingblocks([lastInwpCBG])
check1 = prevInwpCBG.count_orfs_labeled_as_annotated_exon() >\
lastInwpCBG.count_orfs_labeled_as_annotated_exon()
check2 = prevInwpCBG.get_bitscore() > lastInwpCBG.get_bitscore()
check3 = len(prevNodeList) > len(lastNodeList)
check4 = float(lastInwpCBG.count_orfs_labeled_as_annotated_exon()) /\
float(len(GENE_IDENTIFIER_SET)) <= 0.33
if ntdistdict:
check5 = sum(ntdistdict.values())/float(len(ntdistdict)) >\
MIN_INTERGENIC_NT_LENGTH
else:
check5 = False
if tcodedistdict:
check6 = sum(tcodedistdict.values())/float(len(tcodedistdict)) <\
TCODE_MAX_NONCODING
else:
check6 = False
check7 = prevInwpCBG.get_projected_tailing_stop_aa_difference() <\
lastInwpCBG.get_projected_tailing_stop_aa_difference()
check8 = prevInwpCBG.get_projected_tailing_stop_nonaligned_aa_difference()<\
lastInwpCBG.get_projected_tailing_stop_nonaligned_aa_difference()
checklist = [check1,check2,check3,check4,check5,check6,check7,check8]
############################################################################
if verbose: print "NonFinal inwpCBG check:", checklist
############################################################################
if checklist.count(False) == 0:
nonfinalPCG = PacbpCollectionGraph(crossdata={},blastmatrix=PCG._blastmatrix)
# place all PacbPORFs in the nonfinalPCG
for (pacbpkey,nodeQ,nodeS), pacbporf in lastInwpCBG.pacbps.iteritems():
# add to noncodingnongenePCG
nonfinalPCG.add_node(nodeQ)
nonfinalPCG.add_node(nodeS)
nonfinalPCG.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
nonfinalPCG.pacbps[(pacbpkey,nodeQ,nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG,(pacbpkey,nodeQ,nodeS))
# return nonfinalPCG
return nonfinalPCG
else:
return False
def get_frameshifted_cbg(cbg, input, verbose=True):
"""
Get a CBG with frameshifts (in some of if Orfs) compared to this CBG
@type cbg: CodingBlockGraph
@param cbg: CodingBlockGraph to check for frameshifts
@type input: dict
@param input: input <dict data structure> with lists of Orfs
@type verbose: Boolean
@param verbose: print intermediate info to STDOUT for debugging purposes
@rtype: CodingBlockGraph or None
@return: CodingBlockGraph (when existing) or None
"""
# get elegiable lists of Orfs
orfs = _get_elegiable_frameshift_orfsets(cbg, input)
# check how many Orfs are elgiable...
if sum([len(l.orfs) for l in orfs.values()]) == cbg.node_count():
# no frameshift possible here...
return None
# remap the identifiers of the orf objects i.o.t....
multifastas = {}
blastdbs = {}
pacbpcol = PacbpCollectionGraph()
dpcpacbpcol = PacbpCollectionGraph() # ``deepcopied`` variant for pacbps
for org in orfs.keys():
# REMAP fastaheaders as ids to retrieve the Orfs after blast..
for orf in orfs[org].orfs:
orf.fastaheader = str(orf.id)
fname = "%s_frameshiftcbg_%s.mfa" % (org, cbg.barcode())
writeMultiFasta(orfs[org].tofastadict(), fname)
multifastas[org] = fname
########################################################################
if verbose:
print "ORFS:", org, len(orfs[org].orfs),
print[orf.id for orf in orfs[org].orfs],
print[str(orf) for orf in orfs[org].orfs]
########################################################################
for orgQ, orgS in cbg.pairwisecrosscombinations_organism():
# create blastdb if it does not exist yet
if not blastdbs.has_key(orgS):
formatdb(fname=multifastas[orgS])
blastdbs[orgS] = multifastas[orgS]
for orfQ in orfs[orgQ].orfs:
# run blast_seqs2db
blastrec = blastall_seq2db(orfQ.id,
orfQ.protein_sequence,
dbname="./" + blastdbs[orgS])
if len(blastrec.alignments) == 0: continue
for alignment in blastrec.alignments:
# obtain coordinates from sbjct orf identifier
orfid = alignment.title.replace(">", "").split(" ")[0].replace(
"_", "")
orfS = orfs[orgS].get_orf_by_id(int(orfid))
nodeQ = (orgQ, orfQ.id)
nodeS = (orgS, orfS.id)
if nodeQ in cbg.get_nodes() and nodeS in cbg.get_nodes():
pacbporf = cbg.get_pacbps_by_nodes(node1=nodeQ,
node2=nodeS)[0]
else:
# take only the *best* HSP (highest scoring first one)
hsp = alignment.hsps[0]
# correct to absolute positions
hsp.query_start = hsp.query_start + orfQ.protein_startPY
hsp.sbjct_start = hsp.sbjct_start + orfS.protein_startPY
# initialize the PacbP
pacbporf = pacb.conversion.pacbp2pacbporf(
pacb.PacbP(blastp_hsp=hsp), orfQ, orfS)
############################################################
if verbose: print "NEW:", pacbporf
############################################################
uqkey = pacbporf.construct_unique_key(nodeQ, nodeS)
if not nodeQ in pacbpcol.get_nodes(): pacbpcol.add_node(nodeQ)
if not nodeS in pacbpcol.get_nodes(): pacbpcol.add_node(nodeS)
pacbpcol.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
# store to dpcpacbpcol -> pacbpcol is broken in pieces lateron!
dpcpacbpcol.pacbps[(uqkey, nodeQ, nodeS)] = pacbporf
# file cleanup
_file_cleanup(multifastas.values())
_file_cleanup(["formatdb.log"])
_file_cleanup([fname + ".*" for fname in blastdbs.values()])
if not pacbpcol.organism_set_size() == cbg.organism_set_size():
############################################################
if verbose: print "org_set_size() PCG < CBG"
############################################################
# no CBG on the reverse strand
return None
# ``deepcopy`` PacbPcollection
dpcpacbpcol.add_nodes(pacbpcol.get_nodes())
for (uqkey, nodeQ, nodeS) in dpcpacbpcol.pacbps.keys():
(bitscore, length, orfQid, orfSid) = uqkey
dpcpacbpcol.add_edge(nodeQ, nodeS, wt=bitscore)
############################################################################
if verbose:
print pacbpcol, "bitscores:",
print[pacbporf.bitscore for pacbporf in dpcpacbpcol.pacbps.values()]
############################################################################
# do some transformations on the pacbpcol
pacbpcol.remove_low_connectivity_nodes(min_connectivity=cbg.node_count() -
1)
splittedCBGs = pacbpcol.find_fully_connected_subgraphs(
edges=cbg.node_count() - 1, max_missing_edges=0)
# convert to list of CBGs and do some transformations
cbgList = ListOfCodingBlockGraphs(splittedCBGs, input={}, crossdata={})
cbgList.remove_all_but_cbgs()
cbgList.remove_cbgs_with_lt_nodes(cbg.node_count())
cbgList.harvest_pacbps_from_pacbpcollection(dpcpacbpcol)
cbgList.remove_cbgs_without_omsr()
cbgList.update_edge_weights_by_minimal_spanning_range()
cbgList.order_graphlist_by_total_weight_and_identity()
############################################################################
if verbose:
print "FScbgs (%s)" % len(cbgList)
for fscbg in cbgList:
print fscbg
############################################################################
if not cbgList:
# no (better) frameshifted CBG
return None
elif cbgList and not cbgList[0].node_set().symmetric_difference(
cbg.node_set()):
# best CBG is not frameshifted, but CBG itself
return None
else:
# score the difference between the frameshifted and current CBG
score_cbg = cbg.total_weight() * cbg.omsr_identityscore()
score_fscbg = cbgList[0].total_weight(
) * cbgList[0].omsr_identityscore()
# check overlap between the frameshifted and current CBG
a, b, c, d, e, f, g = relatively_positioned_towards(cbgList[0], cbg)
########################################################################
if verbose:
print "CBG", cbg
cbg.printmultiplealignment()
for fscbg in cbgList:
print "fsCBG:", fscbg
fscbg.printmultiplealignment()
########################################################################
if (c, d) == ((0, 0, 1), (1, 0, 0)) or (c, d) == ((0, 0, 1),
(1, 0, 0)):
# CBG and frameshifted CBG do not share a single AA overlap...
# This does not represent a frameshifted CBG as we searched for
return False
elif score_fscbg > score_cbg:
# return the highest scoring, frameshifted CBG
return cbgList[0]
else:
# no, still not convinced that this is a frameshifted CBG
return False
def detect_and_remove_gtgdiscrepancy(inwpcbgs,PCG,GENE_IDENTIFIER_SET,verbose=True):
""" """
# if empty list or empty PCG provided: return False
if not inwpcbgs or not PCG or PCG.node_count() == 0: return False
# get target organism identifier
target = inwpcbgs[0]._get_target_organism()
# Make *the* GTG of the strongest X informant species
# X depends on the maximum number of gene informants (GENE_IDENTIFIER_SET);
# unigene informants are not taken into account here.
# X is defined here by:
# -- at least 3 informants (for very small number of informants)
# -- optimally half of the total numers of informants
# -- at most 8 informants
min_gtg_node_count = 3 + 1
max_gtg_node_count = 8 + 1
gtg_size = min([(len(GENE_IDENTIFIER_SET)-1)/2, max_gtg_node_count])
gtg_size = max([min_gtg_node_count,gtg_size])
btGTG = pcg2gtg_by_bitscore(PCG,target,identifier_list=GENE_IDENTIFIER_SET)
ntGTG = pcg2gtg_by_identity(PCG,target,identifier_list=GENE_IDENTIFIER_SET)
# TEMP solution because OrganismGraph != OrganismStarGraph
# make bitscore ordered list of nodes
bitscore_ordered_nodes = []
for (tNode,iNode),wt in btGTG.weights.iteritems():
if tNode==target: bitscore_ordered_nodes.append( ( wt, iNode ) )
bitscore_ordered_nodes.sort()
#if verbose: print "btGTG::", bitscore_ordered_nodes
while ntGTG.node_count() > gtg_size:
# next line causes errors because OrganismGraph != OrganismStarGraph
# this causes the target node in rare cases to be assigned as the weakest node
# informant = btGTG.weakest_connected_node()
(wt,informant) = bitscore_ordered_nodes.pop(0)
btGTG.del_node(informant)
ntGTG.del_node(informant)
if verbose: print "btGGT.weakest_connected_node() ==", informant, btGTG.get_ordered_nodes()
############################################################################
if verbose:
print "ntGTG:", ntGTG.get_ordered_nodes(),
for node in ntGTG.get_ordered_nodes():
if node == target: continue
print "%1.2f" % ntGTG.weights[(target,node)],
print ""
############################################################################
# detect inwpCBGs which are probably the result of intron alignments
gtgdiscrepancy_internal_inwpcbg_list = assign_internal_nongene_alignments(inwpcbgs,ntGTG)
# detect inwpCBGs with strong discrepancy to this GTG
gtgdiscrepancy_inwpcbg_list = assign_gtgdiscrepancy_inwpcbgs(inwpcbgs,ntGTG)
# merge both lists
if gtgdiscrepancy_internal_inwpcbg_list:
if not gtgdiscrepancy_inwpcbg_list:
gtgdiscrepancy_inwpcbg_list.extend(gtgdiscrepancy_internal_inwpcbg_list)
else:
for inwpcbg in gtgdiscrepancy_internal_inwpcbg_list:
check_str = str(inwpcbg)
if check_str not in [ str(gtgdiscrCBG) for gtgdiscrCBG in gtgdiscrepancy_inwpcbg_list ]:
gtgdiscrepancy_inwpcbg_list.append( inwpcbg )
if not gtgdiscrepancy_inwpcbg_list:
return False
# get list of inwpCBGs that have NO discrepancy
correct_inwpcbg_list = []
check_str_list = []
for discrinwpCBG in gtgdiscrepancy_inwpcbg_list:
check_str_list.append( str(discrinwpCBG) )
for inwpcbg in inwpcbgs:
if str(inwpcbg) not in check_str_list:
correct_inwpcbg_list.append( inwpcbg )
# get all pacbp keys belonging to gtgdiscrepancy inwpcbgs ONLY
gtgdiscrepancy_pacbpkeys = []
for discrinwpCBG in gtgdiscrepancy_inwpcbg_list:
for pacbpkey in discrinwpCBG.pacbps.keys():
# check if this pacbpkey is occuring in a non-removed inwpCBG
is_occurring_in_correct_inwpcbg = False
for inwp in correct_inwpcbg_list:
if pacbpkey in inwp.pacbps.keys():
is_occurring_in_correct_inwpcbg = True
break
# if is_occurring_in_correct_inwpcbg, continue and do not delete
if is_occurring_in_correct_inwpcbg:
continue
# store to gtgdiscrepancy_pacbpkeys when not stored already
if pacbpkey not in gtgdiscrepancy_pacbpkeys:
gtgdiscrepancy_pacbpkeys.append(pacbpkey)
# place all gtgdiscrepancy_pacbpkeys and PacbPORFs in the gtgdiscrepancyPCG
# and, at the same time, remove from the main PCG
gtgdiscrepancyPCG = PacbpCollectionGraph(crossdata={},blastmatrix=PCG._blastmatrix)
for key in gtgdiscrepancy_pacbpkeys:
if key not in PCG.pacbps.keys():
# !?!? TODO why not present in the PCG !?!?!
# anyway, continue here to avoid KeyError
# This PacbPORF was to be deleted rigth here,
# so it is not an extreme disaster. But... scary ;-)
continue
(pacbpkey,nodeQ,nodeS) = key
pacbporf = PCG.pacbps[key]
# add to gtgdiscrepancyPCG
gtgdiscrepancyPCG.add_node(nodeQ)
gtgdiscrepancyPCG.add_node(nodeS)
gtgdiscrepancyPCG.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
gtgdiscrepancyPCG.pacbps[(pacbpkey,nodeQ,nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG,key)
# return gtgdiscrepancyPCG
return gtgdiscrepancyPCG
def detect_and_remove_utrornonegene_inwpcbgs(inwpcbgs,PCG,verbose=True):
""" """
# if empty list or empty PCG provided: return False
if not inwpcbgs or not PCG or PCG.node_count() == 0: return False
# MAKE SHURE ALL Orfs HAVE PREDICTED TSS SITES!!
for inwpCBG in inwpcbgs: inwpCBG.scan_orfs_for_pssm_tss(min_pssm_score=TSS_MIN_PSSM_SCORE)
# get target organism identifier
target = inwpcbgs[0]._get_target_organism()
# detect inwpCBGs which are most likely 5' and 3' non coding or non gene
ncng_5p_list = assign_utrornongene5p_inwpcbgs(inwpcbgs)
ncng_3p_list = assign_utrornongene3p_inwpcbgs(inwpcbgs)
ncng_list = ncng_5p_list
ncng_list.extend(ncng_3p_list)
# return False in no inwpcbgs are assigned
if not ncng_list: return False
# get list of inwpCBGs that are NON ncng
correct_inwpcbg_list = []
check_str_list = []
for discrinwpCBG in ncng_list:
check_str_list.append( str(discrinwpCBG) )
for inwpcbg in inwpcbgs:
if str(inwpcbg) not in check_str_list:
correct_inwpcbg_list.append( inwpcbg )
# get all pacbp keys belonging to noncoding / nongene inwpcbgs ONLY
ncng_pacbpkeys = []
for ncnginwpCBG in ncng_list:
for pacbpkey in ncnginwpCBG.pacbps.keys():
# check if this pacbpkey is occuring in a non-removed inwpCBG
is_occurring_in_correct_inwpcbg = False
for inwp in correct_inwpcbg_list:
if pacbpkey in inwp.pacbps.keys():
is_occurring_in_correct_inwpcbg = True
break
# if is_occurring_in_correct_inwpcbg, continue and do not delete
if is_occurring_in_correct_inwpcbg:
continue
# store to gtgdiscrepancy_pacbpkeys when not stored already
if pacbpkey not in ncng_pacbpkeys:
ncng_pacbpkeys.append(pacbpkey)
# place all ncng_pacbpkeys and PacbPORFs in the noncodingnongenePCG
# and, at the same time, remove from the main PCG
noncodingnongenePCG = PacbpCollectionGraph(crossdata={},blastmatrix=PCG._blastmatrix)
for key in ncng_pacbpkeys:
(pacbpkey,nodeQ,nodeS) = key
pacbporf = PCG.pacbps[key]
# add to noncodingnongenePCG
noncodingnongenePCG.add_node(nodeQ)
noncodingnongenePCG.add_node(nodeS)
noncodingnongenePCG.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
noncodingnongenePCG.pacbps[(pacbpkey,nodeQ,nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG,key)
# return noncodingnongenePCG
return noncodingnongenePCG
def detect_and_remove_synteny(inwpcbgs,
PCG,
GENE_IDENTIFIER_SET,
verbose=True):
""" """
MIN_OBSERVED_VS_EXPECTED_RATIO = 0.20
observed_organism_subcombis = []
syntenic_subinwpcbgs = []
# detect syntenic genes in MAIN inwpCBGs,
# without taking strongest informants by GTG analyses
syntenic_inwpcbgs = assign_syntenic_inwpcbgs(inwpcbgs)
for syntinwpcbg in syntenic_inwpcbgs:
syntenic_subinwpcbgs.append(syntinwpcbg)
for inwpCBG in inwpcbgs:
# omit inwpCBGs with annotated exons/orfs
if inwpCBG.count_orfs_labeled_as_annotated_exon() >= 2: continue
target = inwpCBG._get_target_organism()
# make a (artificially fully connected) GeneTreeGraph
gtg = GeneTreeGraph()
gtg.add_node(target)
for (pacbpkey, nodeQ, nodeS), pacbporf in inwpCBG.pacbps.iteritems():
orgS = inwpCBG.organism_by_node(nodeS)
if orgS not in GENE_IDENTIFIER_SET: continue
gtg.add_node(orgS)
for (pacbpkey, nodeQ, nodeS), pacbporf in inwpCBG.pacbps.iteritems():
orgQ = inwpCBG.organism_by_node(nodeQ)
orgS = inwpCBG.organism_by_node(nodeS)
if orgS not in GENE_IDENTIFIER_SET: continue
gtg.add_edge(orgQ, orgS, wt=pacbporf.bitscore)
# make artificially missed edges between the informants
for org in inwpCBG.organism_set():
if org not in [orgQ, orgS] and org in GENE_IDENTIFIER_SET:
if gtg.has_edge( orgS, org ) and\
gtg.weights[(orgS, org)] > pacbporf.bitscore:
gtg.set_edge_weight(orgS, org, wt=pacbporf.bitscore)
else:
gtg.add_edge(orgS, org, wt=pacbporf.bitscore)
# omit (nearly) empty genetreegraphs
if gtg.node_count() <= 1: continue
# remove (much) weaker connected nodes as expected from the gtg
while gtg.get_nodes() and MIN_OBSERVED_VS_EXPECTED_RATIO >\
min( [ gtg.get_node_weighted_connectivity_observed_vs_expected(node) for node in gtg.get_nodes() ]):
node = gtg.weakest_connected_node()
gtg.del_node(node)
# check if already tested before; present in observed_organism_subcombis
if gtg.get_ordered_nodes() in observed_organism_subcombis: continue
# store to already tested organism subcombinations
observed_organism_subcombis.append(gtg.get_ordered_nodes())
# create a subPCG of these organisms
subPCG = PacbpCollectionGraph(crossdata={},
blastmatrix=PCG._blastmatrix)
for (pacbpkey, nodeQ, nodeS), pacbporf in PCG.pacbps.iteritems():
(orgQ, orfQid), (orgS, orfSid) = nodeQ, nodeS
if orgQ not in gtg.get_nodes(): continue
if orgS not in gtg.get_nodes(): continue
subPCG.add_node(nodeQ)
subPCG.add_node(nodeS)
subPCG.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
subPCG.pacbps[(pacbpkey, nodeQ, nodeS)] = pacbporf
# make inwpCBGs of this subPCG
subinwpcbgs = PCG2inwpCBGS(subPCG)
# check if there are subinwpcbgs
if not subinwpcbgs: continue
########################################################################
#if verbose:
# print "subPCG organism set:", gtg.get_ordered_nodes()
# print_inwpcbgstructure(subinwpcbgs,gtg.get_ordered_nodes())
########################################################################
# create a subInwardsPointingCodingBlockGraph of these organisms
#subinwpCBG = InwardsPointingCodingBlockGraph()
#for (pacbpkey,nodeQ,nodeS), pacbporf in inwpCBG.pacbps.iteritems():
# (orgQ,orfQid),(orgS,orfSid) = nodeQ,nodeS
# if orgQ not in gtg.get_nodes(): continue
# if orgS not in gtg.get_nodes(): continue
# subinwpCBG.add_node(nodeQ)
# subinwpCBG.add_node(nodeS)
# subinwpCBG.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
# subinwpCBG.pacbps[(pacbpkey,nodeQ,nodeS)] = pacbporf
# detect syntenic genes in this subinwpcbgs
syntenic_inwpcbgs = assign_syntenic_inwpcbgs(subinwpcbgs)
for syntinwpcbg in syntenic_inwpcbgs:
syntenic_subinwpcbgs.append(syntinwpcbg)
####################################################################
if verbose:
print "SYNTENIC!!", syntinwpcbg, syntinwpcbg.get_ordered_nodes(
)
for subCBG in subinwpcbgs:
print "syntenic in:", subCBG, subCBG.get_ordered_nodes()
####################################################################
if not syntenic_subinwpcbgs:
return False
# cleanup all inwpCBGs from the syntenic subInwpCBGs
syntenic_pacbpkeys = []
for syntinwpcbg in syntenic_subinwpcbgs:
node_set = syntinwpcbg.node_set()
for inwpCBG in inwpcbgs:
if not node_set.difference(inwpCBG.node_set()):
for pacbpkey in inwpCBG.pacbps.keys():
if pacbpkey not in syntenic_pacbpkeys:
syntenic_pacbpkeys.append(pacbpkey)
# place all syntenic_pacbpkeys and PacbPORFs in the syntenicPCG
# and, at the same time, remove from the main PCG
syntenicPCG = PacbpCollectionGraph(crossdata={},
blastmatrix=PCG._blastmatrix)
for key in syntenic_pacbpkeys:
(pacbpkey, nodeQ, nodeS) = key
pacbporf = PCG.pacbps[key]
# add to syntenicPCG
syntenicPCG.add_node(nodeQ)
syntenicPCG.add_node(nodeS)
syntenicPCG.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
syntenicPCG.pacbps[(pacbpkey, nodeQ, nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG, key)
# return syntenicPCG
return syntenicPCG
def detect_and_remove_single_nonfirst_inwpcbg(inwpcbgs,PCG,GENE_IDENTIFIER_SET,
verbose=False):
"""
Allow deletion of a very shitty, single inwpCBG from the start of the list
"""
# we need at least 2 inwpCBGs in order to remove one of them
if len(inwpcbgs) <= 1: return False
firstInwpCBG = inwpcbgs[0]
nextInwpCBG = inwpcbgs[1]
firstNodeList = [ firstInwpCBG.get_organism_nodes(org)[0] for org in\
firstInwpCBG.organism_set().intersection(GENE_IDENTIFIER_SET) ]
nextNodeList = [ nextInwpCBG.get_organism_nodes(org)[0] for org in\
nextInwpCBG.organism_set().intersection(GENE_IDENTIFIER_SET) ]
# identical nodes -> do not delete. Only go for very obvious things
if Set(firstNodeList).intersection(nextNodeList): return False
ntdistdict = firstInwpCBG.nt_spacing_between_codingblocks([nextInwpCBG])
tcodedistdict = firstInwpCBG.tcode_spacing_between_codingblocks([nextInwpCBG])
# make a long list of checks which should be True in case
# firstInwpCBG is *NOT* the first exon of this gene structure
check1 = nextInwpCBG.count_orfs_labeled_as_annotated_exon() >\
firstInwpCBG.count_orfs_labeled_as_annotated_exon()
check2 = nextInwpCBG.get_bitscore() > firstInwpCBG.get_bitscore()
check3 = len(nextNodeList) > len(firstNodeList)
check4 = float(firstInwpCBG.count_orfs_labeled_as_annotated_exon()) /\
float(len(GENE_IDENTIFIER_SET)) <= 0.33
if ntdistdict:
check5 = sum(ntdistdict.values())/float(len(ntdistdict)) >\
MIN_INTERGENIC_NT_LENGTH
else:
check5 = False
if tcodedistdict:
check6 = sum(tcodedistdict.values())/float(len(tcodedistdict)) <\
TCODE_MAX_NONCODING
else:
check6 = False
check7 = nextInwpCBG.count_orfs_labeled_as_first_exon() >=\
firstInwpCBG.count_orfs_labeled_as_first_exon()
check8 = firstInwpCBG.count_orfs_labeled_as_annotated_exon() == 0
check9 = nextInwpCBG.get_average_upstream_methionine_pssm_score() >\
firstInwpCBG.get_average_upstream_methionine_pssm_score()
checklist = [check1,check2,check3,check4,check5,check6,check7,check8,check9]
############################################################################
if verbose or True: print "NonFirst inwpCBG check:", checklist
############################################################################
if checklist.count(False) <= 1:
nonfirstPCG = PacbpCollectionGraph(crossdata={},blastmatrix=PCG._blastmatrix)
# place all PacbPORFs in the nonfirstPCG
for (pacbpkey,nodeQ,nodeS), pacbporf in firstInwpCBG.pacbps.iteritems():
# add to noncodingnongenePCG
nonfirstPCG.add_node(nodeQ)
nonfirstPCG.add_node(nodeS)
nonfirstPCG.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
nonfirstPCG.pacbps[(pacbpkey,nodeQ,nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG,(pacbpkey,nodeQ,nodeS))
# return nonfirstPCG
return nonfirstPCG
else:
return False
def detect_and_remove_utrornonegene_inwpcbgs(inwpcbgs, PCG, verbose=True):
""" """
# if empty list or empty PCG provided: return False
if not inwpcbgs or not PCG or PCG.node_count() == 0: return False
# MAKE SHURE ALL Orfs HAVE PREDICTED TSS SITES!!
for inwpCBG in inwpcbgs:
inwpCBG.scan_orfs_for_pssm_tss(min_pssm_score=TSS_MIN_PSSM_SCORE)
# get target organism identifier
target = inwpcbgs[0]._get_target_organism()
# detect inwpCBGs which are most likely 5' and 3' non coding or non gene
ncng_5p_list = assign_utrornongene5p_inwpcbgs(inwpcbgs)
ncng_3p_list = assign_utrornongene3p_inwpcbgs(inwpcbgs)
ncng_list = ncng_5p_list
ncng_list.extend(ncng_3p_list)
# return False in no inwpcbgs are assigned
if not ncng_list: return False
# get list of inwpCBGs that are NON ncng
correct_inwpcbg_list = []
check_str_list = []
for discrinwpCBG in ncng_list:
check_str_list.append(str(discrinwpCBG))
for inwpcbg in inwpcbgs:
if str(inwpcbg) not in check_str_list:
correct_inwpcbg_list.append(inwpcbg)
# get all pacbp keys belonging to noncoding / nongene inwpcbgs ONLY
ncng_pacbpkeys = []
for ncnginwpCBG in ncng_list:
for pacbpkey in ncnginwpCBG.pacbps.keys():
# check if this pacbpkey is occuring in a non-removed inwpCBG
is_occurring_in_correct_inwpcbg = False
for inwp in correct_inwpcbg_list:
if pacbpkey in inwp.pacbps.keys():
is_occurring_in_correct_inwpcbg = True
break
# if is_occurring_in_correct_inwpcbg, continue and do not delete
if is_occurring_in_correct_inwpcbg:
continue
# store to gtgdiscrepancy_pacbpkeys when not stored already
if pacbpkey not in ncng_pacbpkeys:
ncng_pacbpkeys.append(pacbpkey)
# place all ncng_pacbpkeys and PacbPORFs in the noncodingnongenePCG
# and, at the same time, remove from the main PCG
noncodingnongenePCG = PacbpCollectionGraph(crossdata={},
blastmatrix=PCG._blastmatrix)
for key in ncng_pacbpkeys:
(pacbpkey, nodeQ, nodeS) = key
pacbporf = PCG.pacbps[key]
# add to noncodingnongenePCG
noncodingnongenePCG.add_node(nodeQ)
noncodingnongenePCG.add_node(nodeS)
noncodingnongenePCG.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
noncodingnongenePCG.pacbps[(pacbpkey, nodeQ, nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG, key)
# return noncodingnongenePCG
return noncodingnongenePCG
def detect_and_remove_single_nonfinal_inwpcbg(inwpcbgs,
PCG,
GENE_IDENTIFIER_SET,
verbose=False):
"""
Allow deletion of a very shitty, single inwpCBG from the end of the list
"""
# we need at least 2 inwpCBGs in order to remove one of them
if len(inwpcbgs) <= 1: return False
lastInwpCBG = inwpcbgs[-1]
prevInwpCBG = inwpcbgs[-2]
lastNodeList = [ lastInwpCBG.get_organism_nodes(org)[0] for org in\
lastInwpCBG.organism_set().intersection(GENE_IDENTIFIER_SET) ]
prevNodeList = [ prevInwpCBG.get_organism_nodes(org)[0] for org in\
prevInwpCBG.organism_set().intersection(GENE_IDENTIFIER_SET) ]
# identical nodes -> do not delete. Only go for very obvious things
if Set(lastNodeList).intersection(prevNodeList): return False
ntdistdict = prevInwpCBG.nt_spacing_between_codingblocks([lastInwpCBG])
tcodedistdict = prevInwpCBG.tcode_spacing_between_codingblocks(
[lastInwpCBG])
check1 = prevInwpCBG.count_orfs_labeled_as_annotated_exon() >\
lastInwpCBG.count_orfs_labeled_as_annotated_exon()
check2 = prevInwpCBG.get_bitscore() > lastInwpCBG.get_bitscore()
check3 = len(prevNodeList) > len(lastNodeList)
check4 = float(lastInwpCBG.count_orfs_labeled_as_annotated_exon()) /\
float(len(GENE_IDENTIFIER_SET)) <= 0.33
if ntdistdict:
check5 = sum(ntdistdict.values())/float(len(ntdistdict)) >\
MIN_INTERGENIC_NT_LENGTH
else:
check5 = False
if tcodedistdict:
check6 = sum(tcodedistdict.values())/float(len(tcodedistdict)) <\
TCODE_MAX_NONCODING
else:
check6 = False
check7 = prevInwpCBG.get_projected_tailing_stop_aa_difference() <\
lastInwpCBG.get_projected_tailing_stop_aa_difference()
check8 = prevInwpCBG.get_projected_tailing_stop_nonaligned_aa_difference()<\
lastInwpCBG.get_projected_tailing_stop_nonaligned_aa_difference()
checklist = [
check1, check2, check3, check4, check5, check6, check7, check8
]
############################################################################
if verbose: print "NonFinal inwpCBG check:", checklist
############################################################################
if checklist.count(False) == 0:
nonfinalPCG = PacbpCollectionGraph(crossdata={},
blastmatrix=PCG._blastmatrix)
# place all PacbPORFs in the nonfinalPCG
for (pacbpkey, nodeQ,
nodeS), pacbporf in lastInwpCBG.pacbps.iteritems():
# add to noncodingnongenePCG
nonfinalPCG.add_node(nodeQ)
nonfinalPCG.add_node(nodeS)
nonfinalPCG.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
nonfinalPCG.pacbps[(pacbpkey, nodeQ, nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG, (pacbpkey, nodeQ, nodeS))
# return nonfinalPCG
return nonfinalPCG
else:
return False
def detect_and_remove_single_nonfirst_inwpcbg(inwpcbgs,
PCG,
GENE_IDENTIFIER_SET,
verbose=False):
"""
Allow deletion of a very shitty, single inwpCBG from the start of the list
"""
# we need at least 2 inwpCBGs in order to remove one of them
if len(inwpcbgs) <= 1: return False
firstInwpCBG = inwpcbgs[0]
nextInwpCBG = inwpcbgs[1]
firstNodeList = [ firstInwpCBG.get_organism_nodes(org)[0] for org in\
firstInwpCBG.organism_set().intersection(GENE_IDENTIFIER_SET) ]
nextNodeList = [ nextInwpCBG.get_organism_nodes(org)[0] for org in\
nextInwpCBG.organism_set().intersection(GENE_IDENTIFIER_SET) ]
# identical nodes -> do not delete. Only go for very obvious things
if Set(firstNodeList).intersection(nextNodeList): return False
ntdistdict = firstInwpCBG.nt_spacing_between_codingblocks([nextInwpCBG])
tcodedistdict = firstInwpCBG.tcode_spacing_between_codingblocks(
[nextInwpCBG])
# make a long list of checks which should be True in case
# firstInwpCBG is *NOT* the first exon of this gene structure
check1 = nextInwpCBG.count_orfs_labeled_as_annotated_exon() >\
firstInwpCBG.count_orfs_labeled_as_annotated_exon()
check2 = nextInwpCBG.get_bitscore() > firstInwpCBG.get_bitscore()
check3 = len(nextNodeList) > len(firstNodeList)
check4 = float(firstInwpCBG.count_orfs_labeled_as_annotated_exon()) /\
float(len(GENE_IDENTIFIER_SET)) <= 0.33
if ntdistdict:
check5 = sum(ntdistdict.values())/float(len(ntdistdict)) >\
MIN_INTERGENIC_NT_LENGTH
else:
check5 = False
if tcodedistdict:
check6 = sum(tcodedistdict.values())/float(len(tcodedistdict)) <\
TCODE_MAX_NONCODING
else:
check6 = False
check7 = nextInwpCBG.count_orfs_labeled_as_first_exon() >=\
firstInwpCBG.count_orfs_labeled_as_first_exon()
check8 = firstInwpCBG.count_orfs_labeled_as_annotated_exon() == 0
check9 = nextInwpCBG.get_average_upstream_methionine_pssm_score() >\
firstInwpCBG.get_average_upstream_methionine_pssm_score()
checklist = [
check1, check2, check3, check4, check5, check6, check7, check8, check9
]
############################################################################
if verbose or True: print "NonFirst inwpCBG check:", checklist
############################################################################
if checklist.count(False) <= 1:
nonfirstPCG = PacbpCollectionGraph(crossdata={},
blastmatrix=PCG._blastmatrix)
# place all PacbPORFs in the nonfirstPCG
for (pacbpkey, nodeQ,
nodeS), pacbporf in firstInwpCBG.pacbps.iteritems():
# add to noncodingnongenePCG
nonfirstPCG.add_node(nodeQ)
nonfirstPCG.add_node(nodeS)
nonfirstPCG.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
nonfirstPCG.pacbps[(pacbpkey, nodeQ, nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG, (pacbpkey, nodeQ, nodeS))
# return nonfirstPCG
return nonfirstPCG
else:
return False
def detect_and_remove_gtgdiscrepancy(inwpcbgs,
PCG,
GENE_IDENTIFIER_SET,
verbose=True):
""" """
# if empty list or empty PCG provided: return False
if not inwpcbgs or not PCG or PCG.node_count() == 0: return False
# get target organism identifier
target = inwpcbgs[0]._get_target_organism()
# Make *the* GTG of the strongest X informant species
# X depends on the maximum number of gene informants (GENE_IDENTIFIER_SET);
# unigene informants are not taken into account here.
# X is defined here by:
# -- at least 3 informants (for very small number of informants)
# -- optimally half of the total numers of informants
# -- at most 8 informants
min_gtg_node_count = 3 + 1
max_gtg_node_count = 8 + 1
gtg_size = min([(len(GENE_IDENTIFIER_SET) - 1) / 2, max_gtg_node_count])
gtg_size = max([min_gtg_node_count, gtg_size])
btGTG = pcg2gtg_by_bitscore(PCG,
target,
identifier_list=GENE_IDENTIFIER_SET)
ntGTG = pcg2gtg_by_identity(PCG,
target,
identifier_list=GENE_IDENTIFIER_SET)
# TEMP solution because OrganismGraph != OrganismStarGraph
# make bitscore ordered list of nodes
bitscore_ordered_nodes = []
for (tNode, iNode), wt in btGTG.weights.iteritems():
if tNode == target: bitscore_ordered_nodes.append((wt, iNode))
bitscore_ordered_nodes.sort()
#if verbose: print "btGTG::", bitscore_ordered_nodes
while ntGTG.node_count() > gtg_size:
# next line causes errors because OrganismGraph != OrganismStarGraph
# this causes the target node in rare cases to be assigned as the weakest node
# informant = btGTG.weakest_connected_node()
(wt, informant) = bitscore_ordered_nodes.pop(0)
btGTG.del_node(informant)
ntGTG.del_node(informant)
if verbose:
print "btGGT.weakest_connected_node() ==", informant, btGTG.get_ordered_nodes(
)
############################################################################
if verbose:
print "ntGTG:", ntGTG.get_ordered_nodes(),
for node in ntGTG.get_ordered_nodes():
if node == target: continue
print "%1.2f" % ntGTG.weights[(target, node)],
print ""
############################################################################
# detect inwpCBGs which are probably the result of intron alignments
gtgdiscrepancy_internal_inwpcbg_list = assign_internal_nongene_alignments(
inwpcbgs, ntGTG)
# detect inwpCBGs with strong discrepancy to this GTG
gtgdiscrepancy_inwpcbg_list = assign_gtgdiscrepancy_inwpcbgs(
inwpcbgs, ntGTG)
# merge both lists
if gtgdiscrepancy_internal_inwpcbg_list:
if not gtgdiscrepancy_inwpcbg_list:
gtgdiscrepancy_inwpcbg_list.extend(
gtgdiscrepancy_internal_inwpcbg_list)
else:
for inwpcbg in gtgdiscrepancy_internal_inwpcbg_list:
check_str = str(inwpcbg)
if check_str not in [
str(gtgdiscrCBG)
for gtgdiscrCBG in gtgdiscrepancy_inwpcbg_list
]:
gtgdiscrepancy_inwpcbg_list.append(inwpcbg)
if not gtgdiscrepancy_inwpcbg_list:
return False
# get list of inwpCBGs that have NO discrepancy
correct_inwpcbg_list = []
check_str_list = []
for discrinwpCBG in gtgdiscrepancy_inwpcbg_list:
check_str_list.append(str(discrinwpCBG))
for inwpcbg in inwpcbgs:
if str(inwpcbg) not in check_str_list:
correct_inwpcbg_list.append(inwpcbg)
# get all pacbp keys belonging to gtgdiscrepancy inwpcbgs ONLY
gtgdiscrepancy_pacbpkeys = []
for discrinwpCBG in gtgdiscrepancy_inwpcbg_list:
for pacbpkey in discrinwpCBG.pacbps.keys():
# check if this pacbpkey is occuring in a non-removed inwpCBG
is_occurring_in_correct_inwpcbg = False
for inwp in correct_inwpcbg_list:
if pacbpkey in inwp.pacbps.keys():
is_occurring_in_correct_inwpcbg = True
break
# if is_occurring_in_correct_inwpcbg, continue and do not delete
if is_occurring_in_correct_inwpcbg:
continue
# store to gtgdiscrepancy_pacbpkeys when not stored already
if pacbpkey not in gtgdiscrepancy_pacbpkeys:
gtgdiscrepancy_pacbpkeys.append(pacbpkey)
# place all gtgdiscrepancy_pacbpkeys and PacbPORFs in the gtgdiscrepancyPCG
# and, at the same time, remove from the main PCG
gtgdiscrepancyPCG = PacbpCollectionGraph(crossdata={},
blastmatrix=PCG._blastmatrix)
for key in gtgdiscrepancy_pacbpkeys:
if key not in PCG.pacbps.keys():
# !?!? TODO why not present in the PCG !?!?!
# anyway, continue here to avoid KeyError
# This PacbPORF was to be deleted rigth here,
# so it is not an extreme disaster. But... scary ;-)
continue
(pacbpkey, nodeQ, nodeS) = key
pacbporf = PCG.pacbps[key]
# add to gtgdiscrepancyPCG
gtgdiscrepancyPCG.add_node(nodeQ)
gtgdiscrepancyPCG.add_node(nodeS)
gtgdiscrepancyPCG.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
gtgdiscrepancyPCG.pacbps[(pacbpkey, nodeQ, nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG, key)
# return gtgdiscrepancyPCG
return gtgdiscrepancyPCG
def blastanalysescbgjunction(
gsg,
prevCBG,
nextCBG,
omit_cbg_orfs=False,
omit_non_cbg_orfs=False,
extra_blastp_params=CBG_JUNCTION_BLAST2PACBPCOL_EXTRA_BLASTP_PARAMS,
omsr_2_mask_aa_length_correction=CBG_JUNCTION_BLAST2PACBPCOL_OMSR_2_AA_MASK,
verbose=False):
"""
"""
############################################################
if verbose:
stw = StopWatch('blastanalysescbgjunction')
stw.start()
############################################################
orfs = {}
if not omit_cbg_orfs:
# gather Orfs from prevCBG and nextCBG
for org, orflist, in prevCBG.get_orfs_of_graph().iteritems():
orf = orflist[0]
orfs[(org, orf.id)] = orf
for org, orflist, in nextCBG.get_orfs_of_graph().iteritems():
orf = orflist[0]
orfs[(org, orf.id)] = orf
############################################################
if verbose:
print stw.lap(), "orfs (1):", len(orfs)
print _format_orf_nodes_to_string(orfs.keys())
############################################################
# create masked fasta database in a dict
fastadbmfa = parseFasta(
create_hmmdb_for_neighbouring_cbgs(
gsg.input,
prevCBG,
nextCBG,
omsr_2_mask_aa_length_correction=omsr_2_mask_aa_length_correction,
).split("\n"))
############################################################
if verbose: print stw.lap(), "fasta db (1):", len(fastadbmfa)
############################################################
# remove ORFs that do not belong to prevCBG and nextCBG,
# or that DO belong to prevCBG and nextCBG, or neither
fastaheaders = fastadbmfa.keys()
for header in fastaheaders:
org, orfid = header.split("_orf_")
orfid = int(orfid)
node = (org, orfid)
# check for the omit_non_cbg_orfs criterion
add_orf = False
if omit_non_cbg_orfs:
if node not in orfs:
del (fastadbmfa[header])
else:
add_orf = True
# check for the omit_cbg_orfs criterion
if omit_cbg_orfs and node in orfs:
del (fastadbmfa[header])
if add_orf:
# get this Orf and add to orfs
orfs[node] = gsg.input[org]['orfs'].get_orf_by_id(orfid)
############################################################
if verbose:
print stw.lap(), "fasta db (2):", len(fastadbmfa)
print _format_fastadbmfa_nodes_to_string(fastadbmfa.keys())
############################################################
############################################################
if verbose:
print stw.lap(), "orfs (2):", len(orfs)
print _format_orf_nodes_to_string(orfs.keys())
############################################################
# no query/sbjct range left at all
if not fastadbmfa: return []
# check if all organisms are still covered
orgSet = Set([k.split("_orf_")[0] for k in fastadbmfa.keys()])
if orgSet.symmetric_difference(gsg.organism_set()):
return []
# create !single! fasta database
fastadbname = prevCBG.barcode() + "_" + nextCBG.barcode() + ".mfa"
writeMultiFasta(fastadbmfa, fastadbname)
formatdb(fname=fastadbname)
# remap the identifiers of the orf objects i.o.t....
multifastas = {}
blastdbs = {}
pacbpcol = PacbpCollectionGraph()
dpcpacbpcol = PacbpCollectionGraph() # ``deepcopied`` variant for pacbps
############################################################
if verbose: print stw.lap(), "blastp starting"
############################################################
for orgQ, orgS in prevCBG.pairwisecrosscombinations_organism():
for nodeQ, orfQ in orfs.iteritems():
# only blast the (masked) Orfs of orgQ
if prevCBG.organism_by_node(nodeQ) != orgQ: continue
# get the masked protein sequence of this orfObj
header = orgQ + "_orf_" + str(orfQ.id)
# check if key exists in fastadbmfa. In a case where
# an Orf is masked out completely, it is absent here!
if not fastadbmfa.has_key(header): continue
protseq = fastadbmfa[orgQ + "_orf_" + str(orfQ.id)]
# run blast_seqs2db
blastrec = blastall_seq2db(orfQ.id,
protseq,
fastadbname,
extra_blastp_params=extra_blastp_params)
# omit empty blast records
if len(blastrec.alignments) == 0: continue
for alignment in blastrec.alignments:
# get sbjct Org and Orf identifiers
_orgS, _orfSid = alignment.title.replace(">",
"").split("_orf_")
if _orgS != orgS: continue
nodeS = (_orgS, int(_orfSid))
orfS = orfs[nodeS]
# take only the *best* HSP (highest scoring first one)
hsp = alignment.hsps[0]
# correct to absolute positions
hsp.query_start = hsp.query_start + orfQ.protein_startPY
hsp.sbjct_start = hsp.sbjct_start + orfS.protein_startPY
# initialize the PacbP
pacbporf = pacb.conversion.pacbp2pacbporf(
pacb.PacbP(blastp_hsp=hsp), orfQ, orfS)
################################################################
if verbose:
print pacbporf, orgQ, orgS, orfQ
print pacbporf.query
print pacbporf.match
print pacbporf.sbjct
################################################################
# create nodes; ( Organism Identifier, Orf Identifier )
nodeQ = (orgQ, orfQ.id)
nodeS = (orgS, orfS.id)
uqkey = pacbporf.construct_unique_key(nodeQ, nodeS)
if not nodeQ in pacbpcol.get_nodes(): pacbpcol.add_node(nodeQ)
if not nodeS in pacbpcol.get_nodes(): pacbpcol.add_node(nodeS)
pacbpcol.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
# store to dpcpacbpcol -> pacbpcol is broken in pieces lateron!
dpcpacbpcol.pacbps[(uqkey, nodeQ, nodeS)] = pacbporf
############################################################
if verbose: print stw.lap(), "blastp done"
############################################################
# file cleanup
_file_cleanup(multifastas.values())
_file_cleanup(["formatdb.log"])
_file_cleanup([fname + ".*" for fname in blastdbs.values()])
# check if all Organism/Gene identifiers are covered in PacbPs
if not pacbpcol.organism_set_size() == gsg.organism_set_size():
return []
# ``deepcopy`` PacbPcollection pacbpcol to dpcpacbpcol
# In dpcpacbpcol the actual PacbPORFs are stores & kept,
# whereas pacbpcol itself is splitted in CBGs (which
# function does not yet (!?) take the actual pacbps into account)
dpcpacbpcol.add_nodes(pacbpcol.get_nodes())
for (uqkey, nodeQ, nodeS) in dpcpacbpcol.pacbps.keys():
(bitscore, length, orfQid, orfSid) = uqkey
dpcpacbpcol.add_edge(nodeQ, nodeS, wt=bitscore)
################################################################
if verbose:
print pacbpcol
print "PCG bitscores:",
print[p.bitscore for p in dpcpacbpcol.pacbps.values()]
print "PCG nodes:", dpcpacbpcol.get_ordered_nodes()
################################################################
#### do some transformations on the pacbpcol
####pacbpcol.remove_low_connectivity_nodes(min_connectivity=gsg.EXACT_SG_NODE_COUNT-1)
####splittedCBGs = pacbpcol.find_fully_connected_subgraphs(
#### edges=gsg.node_count()-1 , max_missing_edges=0 )
##### convert to list of CBGs and do some transformations
####cbgList = ListOfCodingBlockGraphs(splittedCBGs,input={},crossdata={})
####cbgList.remove_all_but_complete_cbgs()
####cbgList.remove_cbgs_with_lt_nodes(gsg.EXACT_SG_NODE_COUNT)
####cbgList.harvest_pacbps_from_pacbpcollection(dpcpacbpcol)
####cbgList.remove_cbgs_without_omsr()
####cbgList.update_edge_weights_by_minimal_spanning_range()
####cbgList.order_list_by_attribute(order_by='total_weight',reversed=True)
min_connectivity = max([1, gsg.EXACT_SG_NODE_COUNT - 1 - 2])
pacbpcol.remove_low_connectivity_nodes(min_connectivity=min_connectivity)
max_missing_edges = gsg.EXACT_SG_NODE_COUNT - 3
splittedCBGs = pacbpcol.find_fully_connected_subgraphs(
edges=gsg.node_count() - 1, max_missing_edges=max_missing_edges)
# convert to list of CBGs and do some transformations
cbgList = ListOfCodingBlockGraphs(splittedCBGs, input={}, crossdata={})
cbgList.remove_all_but_cbgs()
cbgList.harvest_pacbps_from_pacbpcollection(dpcpacbpcol)
cbgList.make_pacbps_for_missing_edges()
cbgList.remove_all_but_complete_cbgs()
cbgList.remove_cbgs_with_lt_nodes(gsg.EXACT_SG_NODE_COUNT)
cbgList.remove_cbgs_without_omsr()
cbgList.update_edge_weights_by_minimal_spanning_range()
cbgList.order_list_by_attribute(order_by='total_weight', reversed=True)
# and create_cache() for these CBGs
for cbg in cbgList:
cbg.create_cache()
####################################################################
if verbose:
print stw.lap(), "CBGs created", len(cbgList)
for newcbg in cbgList:
print "new:", newcbg
####################################################################
# return list with CBGs
return cbgList.codingblockgraphs
def get_reverse_cbg(cbg, frame, verbose=False):
"""
Get the ReversecomplementCodingBlockGraph in requested frame of this CBG
@type cbg: CodingBlockGraph
@param cbg: CodingBlockGraph to reversecomplement
@type frame: integer
@param frame: 0,1 or 2
@type verbose: Boolean
@param verbose: print intermediate info to STDOUT for debugging purposes
@rtype: ReversecomplementCodingBlockGraph or None
@return: ReversecomplementCodingBlockGraph (when existing) or None
"""
min_orf_length = (cbg.omsrlength() / 2) * 3
orfs = get_reverse_strand_orfsets(cbg,
frame,
min_orf_length=min_orf_length)
# remap the identifiers of the orf objects i.o.t....
multifastas = {}
blastdbs = {}
pacbpcol = PacbpCollectionGraph()
dpcpacbpcol = PacbpCollectionGraph() # ``deepcopied`` variant for pacbps
for org in orfs.keys():
fname = "%s_reversecbg_%s.mfa" % (org, cbg.barcode())
writeMultiFasta(orfs[org].tofastadict(), fname)
multifastas[org] = fname
########################################################################
if verbose:
print "ORFS:", org, len(orfs[org].orfs),
print[len(o.protein_sequence) for o in orfs[org].orfs]
########################################################################
revpacbps = {}
for orgQ, orgS in cbg.pairwisecrosscombinations_organism():
# create blastdb if it does not exist yet
if not blastdbs.has_key(orgS):
formatdb(fname=multifastas[orgS])
blastdbs[orgS] = multifastas[orgS]
revpacbporfs = {}
for orfQ in orfs[orgQ].orfs:
# run blast_seqs2db
blastrec = blastall_seq2db(orfQ.id,
orfQ.protein_sequence,
dbname="./" + blastdbs[orgS])
if len(blastrec.alignments) == 0: continue
for alignment in blastrec.alignments:
# obtain coordinates from sbjct orf identifier
orfS = orfs[orgS].get_orf_by_id(
alignment.title.replace(">", ""))
# take only the *best* HSP (highest scoring first one)
hsp = alignment.hsps[0]
# skip if hsp is very short
if len(hsp.query) < cbg.omsrlength() / 2: continue
# correct to absolute positions
hsp.query_start = hsp.query_start + orfQ.protein_startPY
hsp.sbjct_start = hsp.sbjct_start + orfS.protein_startPY
# initialize the PacbP
pacbporf = pacb.conversion.pacbp2pacbporf(
pacb.PacbP(blastp_hsp=hsp), orfQ, orfS)
################################################################
if verbose:
print pacbporf, orgQ, orgS, orfQ
print pacbporf.query
print pacbporf.match
print pacbporf.sbjct
###pacbporf.print_protein_and_dna()
################################################################
nodeQ = (orgQ, orfQ.protein_startPY)
nodeS = (orgS, orfS.protein_startPY)
uqkey = pacbporf.construct_unique_key(nodeQ, nodeS)
if not nodeQ in pacbpcol.get_nodes(): pacbpcol.add_node(nodeQ)
if not nodeS in pacbpcol.get_nodes(): pacbpcol.add_node(nodeS)
pacbpcol.add_edge(nodeQ, nodeS, wt=pacbporf.bitscore)
# store to dpcpacbpcol -> pacbpcol is broken in pieces lateron!
dpcpacbpcol.pacbps[(uqkey, nodeQ, nodeS)] = pacbporf
# file cleanup
_file_cleanup(multifastas.values())
_file_cleanup(["formatdb.log"])
_file_cleanup([fname + ".*" for fname in blastdbs.values()])
if not pacbpcol.organism_set_size() == cbg.organism_set_size():
# no CBG on the reverse strand
return None
# ``deepcopy`` PacbPcollection
dpcpacbpcol.add_nodes(pacbpcol.get_nodes())
for (uqkey, nodeQ, nodeS) in dpcpacbpcol.pacbps.keys():
(bitscore, length, orfQid, orfSid) = uqkey
dpcpacbpcol.add_edge(nodeQ, nodeS, wt=bitscore)
############################################################################
if verbose:
print pacbpcol, "bitscores:",
print[pacbporf.bitscore for pacbporf in dpcpacbpcol.pacbps.values()]
############################################################################
# do some transformations on the pacbpcol
pacbpcol.remove_low_connectivity_nodes(min_connectivity=cbg.node_count() -
1)
splittedCBGs = pacbpcol.find_fully_connected_subgraphs(
edges=cbg.node_count() - 1, max_missing_edges=0)
# convert to list of CBGs and do some transformations
cbgList = ListOfCodingBlockGraphs(splittedCBGs, input={}, crossdata={})
cbgList.remove_all_but_complete_cbgs()
cbgList.harvest_pacbps_from_pacbpcollection(dpcpacbpcol)
cbgList.remove_cbgs_without_omsr()
cbgList.update_edge_weights_by_minimal_spanning_range()
cbgList.order_list_by_attribute(order_by='total_weight', reversed=True)
############################################################################
if verbose:
for revcbg in cbgList:
print "revCBG:", revcbg
############################################################################
if not cbgList:
# no CBG on the reverse strand
return None
else:
# return the highest scoring CBG as a ReversecomlementCodingBlockGraph
return CodingBlockGraph2ReversecomlementCodingBlockGraph(
cbgList.codingblockgraphs[0])
def blastanalysescbgjunction(gsg,prevCBG,nextCBG,
omit_cbg_orfs = False,
omit_non_cbg_orfs = False,
extra_blastp_params=CBG_JUNCTION_BLAST2PACBPCOL_EXTRA_BLASTP_PARAMS,
omsr_2_mask_aa_length_correction=CBG_JUNCTION_BLAST2PACBPCOL_OMSR_2_AA_MASK,
verbose=False):
"""
"""
############################################################
if verbose:
stw = StopWatch('blastanalysescbgjunction')
stw.start()
############################################################
orfs = {}
if not omit_cbg_orfs:
# gather Orfs from prevCBG and nextCBG
for org,orflist, in prevCBG.get_orfs_of_graph().iteritems():
orf = orflist[0]
orfs[(org,orf.id)] = orf
for org,orflist, in nextCBG.get_orfs_of_graph().iteritems():
orf = orflist[0]
orfs[(org,orf.id)] = orf
############################################################
if verbose:
print stw.lap(), "orfs (1):",len(orfs)
print _format_orf_nodes_to_string(orfs.keys())
############################################################
# create masked fasta database in a dict
fastadbmfa = parseFasta(
create_hmmdb_for_neighbouring_cbgs(
gsg.input,prevCBG,nextCBG,
omsr_2_mask_aa_length_correction=omsr_2_mask_aa_length_correction,
).split("\n")
)
############################################################
if verbose: print stw.lap(), "fasta db (1):",len(fastadbmfa)
############################################################
# remove ORFs that do not belong to prevCBG and nextCBG,
# or that DO belong to prevCBG and nextCBG, or neither
fastaheaders = fastadbmfa.keys()
for header in fastaheaders:
org,orfid = header.split("_orf_")
orfid = int(orfid)
node = (org,orfid)
# check for the omit_non_cbg_orfs criterion
add_orf = False
if omit_non_cbg_orfs:
if node not in orfs:
del(fastadbmfa[header])
else:
add_orf = True
# check for the omit_cbg_orfs criterion
if omit_cbg_orfs and node in orfs:
del(fastadbmfa[header])
if add_orf:
# get this Orf and add to orfs
orfs[node] = gsg.input[org]['orfs'].get_orf_by_id(orfid)
############################################################
if verbose:
print stw.lap(), "fasta db (2):",len(fastadbmfa)
print _format_fastadbmfa_nodes_to_string(fastadbmfa.keys())
############################################################
############################################################
if verbose:
print stw.lap(), "orfs (2):",len(orfs)
print _format_orf_nodes_to_string(orfs.keys())
############################################################
# no query/sbjct range left at all
if not fastadbmfa: return []
# check if all organisms are still covered
orgSet = Set([ k.split("_orf_")[0] for k in fastadbmfa.keys()])
if orgSet.symmetric_difference(gsg.organism_set()):
return []
# create !single! fasta database
fastadbname = prevCBG.barcode()+"_"+nextCBG.barcode()+".mfa"
writeMultiFasta(fastadbmfa,fastadbname)
formatdb(fname=fastadbname)
# remap the identifiers of the orf objects i.o.t....
multifastas = {}
blastdbs = {}
pacbpcol = PacbpCollectionGraph()
dpcpacbpcol = PacbpCollectionGraph() # ``deepcopied`` variant for pacbps
############################################################
if verbose: print stw.lap(), "blastp starting"
############################################################
for orgQ,orgS in prevCBG.pairwisecrosscombinations_organism():
for nodeQ,orfQ in orfs.iteritems():
# only blast the (masked) Orfs of orgQ
if prevCBG.organism_by_node(nodeQ) != orgQ: continue
# get the masked protein sequence of this orfObj
header = orgQ+"_orf_"+str(orfQ.id)
# check if key exists in fastadbmfa. In a case where
# an Orf is masked out completely, it is absent here!
if not fastadbmfa.has_key(header): continue
protseq = fastadbmfa[orgQ+"_orf_"+str(orfQ.id)]
# run blast_seqs2db
blastrec = blastall_seq2db(orfQ.id,protseq,fastadbname,
extra_blastp_params=extra_blastp_params)
# omit empty blast records
if len(blastrec.alignments) == 0: continue
for alignment in blastrec.alignments:
# get sbjct Org and Orf identifiers
_orgS,_orfSid = alignment.title.replace(">","").split("_orf_")
if _orgS != orgS: continue
nodeS = (_orgS,int(_orfSid))
orfS = orfs[nodeS]
# take only the *best* HSP (highest scoring first one)
hsp = alignment.hsps[0]
# correct to absolute positions
hsp.query_start = hsp.query_start + orfQ.protein_startPY
hsp.sbjct_start = hsp.sbjct_start + orfS.protein_startPY
# initialize the PacbP
pacbporf = pacb.conversion.pacbp2pacbporf(
pacb.PacbP(blastp_hsp=hsp),orfQ,orfS)
################################################################
if verbose:
print pacbporf, orgQ,orgS, orfQ
print pacbporf.query
print pacbporf.match
print pacbporf.sbjct
################################################################
# create nodes; ( Organism Identifier, Orf Identifier )
nodeQ = ( orgQ, orfQ.id )
nodeS = ( orgS, orfS.id )
uqkey = pacbporf.construct_unique_key(nodeQ,nodeS)
if not nodeQ in pacbpcol.get_nodes(): pacbpcol.add_node(nodeQ)
if not nodeS in pacbpcol.get_nodes(): pacbpcol.add_node(nodeS)
pacbpcol.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
# store to dpcpacbpcol -> pacbpcol is broken in pieces lateron!
dpcpacbpcol.pacbps[(uqkey,nodeQ,nodeS)] = pacbporf
############################################################
if verbose: print stw.lap(), "blastp done"
############################################################
# file cleanup
_file_cleanup(multifastas.values())
_file_cleanup(["formatdb.log"])
_file_cleanup([ fname+".*" for fname in blastdbs.values()])
# check if all Organism/Gene identifiers are covered in PacbPs
if not pacbpcol.organism_set_size() == gsg.organism_set_size():
return []
# ``deepcopy`` PacbPcollection pacbpcol to dpcpacbpcol
# In dpcpacbpcol the actual PacbPORFs are stores & kept,
# whereas pacbpcol itself is splitted in CBGs (which
# function does not yet (!?) take the actual pacbps into account)
dpcpacbpcol.add_nodes( pacbpcol.get_nodes() )
for (uqkey,nodeQ,nodeS) in dpcpacbpcol.pacbps.keys():
(bitscore,length,orfQid,orfSid) = uqkey
dpcpacbpcol.add_edge(nodeQ,nodeS,wt=bitscore)
################################################################
if verbose:
print pacbpcol
print "PCG bitscores:",
print [ p.bitscore for p in dpcpacbpcol.pacbps.values() ]
def detect_and_remove_synteny(inwpcbgs,PCG,GENE_IDENTIFIER_SET,verbose=True):
""" """
MIN_OBSERVED_VS_EXPECTED_RATIO = 0.20
observed_organism_subcombis = []
syntenic_subinwpcbgs = []
# detect syntenic genes in MAIN inwpCBGs,
# without taking strongest informants by GTG analyses
syntenic_inwpcbgs = assign_syntenic_inwpcbgs(inwpcbgs)
for syntinwpcbg in syntenic_inwpcbgs:
syntenic_subinwpcbgs.append(syntinwpcbg)
for inwpCBG in inwpcbgs:
# omit inwpCBGs with annotated exons/orfs
if inwpCBG.count_orfs_labeled_as_annotated_exon() >= 2: continue
target = inwpCBG._get_target_organism()
# make a (artificially fully connected) GeneTreeGraph
gtg = GeneTreeGraph()
gtg.add_node(target)
for (pacbpkey,nodeQ,nodeS),pacbporf in inwpCBG.pacbps.iteritems():
orgS = inwpCBG.organism_by_node(nodeS)
if orgS not in GENE_IDENTIFIER_SET: continue
gtg.add_node(orgS)
for (pacbpkey,nodeQ,nodeS),pacbporf in inwpCBG.pacbps.iteritems():
orgQ = inwpCBG.organism_by_node(nodeQ)
orgS = inwpCBG.organism_by_node(nodeS)
if orgS not in GENE_IDENTIFIER_SET: continue
gtg.add_edge( orgQ, orgS, wt = pacbporf.bitscore )
# make artificially missed edges between the informants
for org in inwpCBG.organism_set():
if org not in [orgQ,orgS] and org in GENE_IDENTIFIER_SET:
if gtg.has_edge( orgS, org ) and\
gtg.weights[(orgS, org)] > pacbporf.bitscore:
gtg.set_edge_weight(orgS,org,wt = pacbporf.bitscore)
else:
gtg.add_edge( orgS, org, wt = pacbporf.bitscore )
# omit (nearly) empty genetreegraphs
if gtg.node_count() <= 1: continue
# remove (much) weaker connected nodes as expected from the gtg
while gtg.get_nodes() and MIN_OBSERVED_VS_EXPECTED_RATIO >\
min( [ gtg.get_node_weighted_connectivity_observed_vs_expected(node) for node in gtg.get_nodes() ]):
node = gtg.weakest_connected_node()
gtg.del_node(node)
# check if already tested before; present in observed_organism_subcombis
if gtg.get_ordered_nodes() in observed_organism_subcombis: continue
# store to already tested organism subcombinations
observed_organism_subcombis.append( gtg.get_ordered_nodes() )
# create a subPCG of these organisms
subPCG = PacbpCollectionGraph(crossdata={},
blastmatrix=PCG._blastmatrix)
for (pacbpkey,nodeQ,nodeS), pacbporf in PCG.pacbps.iteritems():
(orgQ,orfQid),(orgS,orfSid) = nodeQ,nodeS
if orgQ not in gtg.get_nodes(): continue
if orgS not in gtg.get_nodes(): continue
subPCG.add_node(nodeQ)
subPCG.add_node(nodeS)
subPCG.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
subPCG.pacbps[(pacbpkey,nodeQ,nodeS)] = pacbporf
# make inwpCBGs of this subPCG
subinwpcbgs = PCG2inwpCBGS(subPCG)
# check if there are subinwpcbgs
if not subinwpcbgs: continue
########################################################################
#if verbose:
# print "subPCG organism set:", gtg.get_ordered_nodes()
# print_inwpcbgstructure(subinwpcbgs,gtg.get_ordered_nodes())
########################################################################
# create a subInwardsPointingCodingBlockGraph of these organisms
#subinwpCBG = InwardsPointingCodingBlockGraph()
#for (pacbpkey,nodeQ,nodeS), pacbporf in inwpCBG.pacbps.iteritems():
# (orgQ,orfQid),(orgS,orfSid) = nodeQ,nodeS
# if orgQ not in gtg.get_nodes(): continue
# if orgS not in gtg.get_nodes(): continue
# subinwpCBG.add_node(nodeQ)
# subinwpCBG.add_node(nodeS)
# subinwpCBG.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
# subinwpCBG.pacbps[(pacbpkey,nodeQ,nodeS)] = pacbporf
# detect syntenic genes in this subinwpcbgs
syntenic_inwpcbgs = assign_syntenic_inwpcbgs(subinwpcbgs)
for syntinwpcbg in syntenic_inwpcbgs:
syntenic_subinwpcbgs.append(syntinwpcbg)
####################################################################
if verbose:
print "SYNTENIC!!", syntinwpcbg, syntinwpcbg.get_ordered_nodes()
for subCBG in subinwpcbgs:
print "syntenic in:", subCBG, subCBG.get_ordered_nodes()
####################################################################
if not syntenic_subinwpcbgs:
return False
# cleanup all inwpCBGs from the syntenic subInwpCBGs
syntenic_pacbpkeys = []
for syntinwpcbg in syntenic_subinwpcbgs:
node_set = syntinwpcbg.node_set()
for inwpCBG in inwpcbgs:
if not node_set.difference(inwpCBG.node_set()):
for pacbpkey in inwpCBG.pacbps.keys():
if pacbpkey not in syntenic_pacbpkeys:
syntenic_pacbpkeys.append(pacbpkey)
# place all syntenic_pacbpkeys and PacbPORFs in the syntenicPCG
# and, at the same time, remove from the main PCG
syntenicPCG = PacbpCollectionGraph(crossdata={},blastmatrix=PCG._blastmatrix)
for key in syntenic_pacbpkeys:
(pacbpkey,nodeQ,nodeS) = key
pacbporf = PCG.pacbps[key]
# add to syntenicPCG
syntenicPCG.add_node(nodeQ)
syntenicPCG.add_node(nodeS)
syntenicPCG.add_edge(nodeQ,nodeS,wt=pacbporf.bitscore)
syntenicPCG.pacbps[(pacbpkey,nodeQ,nodeS)] = pacbporf
# remove from main PCG
_delete_pacbp(PCG,key)
# return syntenicPCG
return syntenicPCG
def create_pacbpcollectiongraph_from_crossdata(
crossdata,
increment_to_graph=None):
"""
Create (incremental) PacbpCollectionGraph from crossdata dict structure
@type crossdata: dict
@param crossdata: crossdata <dict data structure>
@type increment_to_graph: None or PacbpCollectionGraph
@param increment_to_graph: when applied, increment crossdata to applied PCG
@rtype g: PacbpCollectionGraph
@return g: PacbpCollectionGraph
"""
if increment_to_graph:
# add new nodes to existing graph
g = increment_to_graph
else:
# create a new blank graph
from graphAbgp import PacbpCollectionGraph
g = PacbpCollectionGraph()
for (orgA,orgB) in crossdata.keys():
keys = crossdata[(orgA,orgB)]['accepted_pacbs'].keys()
# sort keys in order to start with highest bitscore
keys.sort()
keys.reverse()
for key in keys:
(bitscore,lenght,pointerA,pointerB) = key
nodeA = (orgA,pointerA)
nodeB = (orgB,pointerB)
# check if (org,ORF) node exist already
if nodeA not in g.get_nodes(): g.add_node(nodeA)
if nodeB not in g.get_nodes(): g.add_node(nodeB)
if g.has_edge(nodeA,nodeB):
wt = g.get_edge_weight(nodeA,nodeB)
if bitscore > wt:
g.set_edge_weight(nodeA,nodeB,bitscore)
else:
pass
else:
# and create a new edge
g.add_edge(nodeA,nodeB,wt=bitscore)
# ready!
return g
