def assign_utrornongene3p_inwpcbgs(inwpcbgs,verbose=True):
""" """
# return empty list when no inwpcbgs applied
if not inwpcbgs: return []
# get most likely first & final inwpCBG pointer in inwpcbgs list
posFirst,posFinal = get_first_and_final_inwpcbg_pos(inwpcbgs)
# return variable list
noncoding_inwpcbg_list = []
# get data of most likely first inwpCBG
max_cntAnnot = max([inwp.count_orfs_labeled_as_annotated_exon() for inwp in inwpcbgs ])
finalInwpCBG = inwpcbgs[posFinal]
final_cnt_is_final = finalInwpCBG.count_orfs_labeled_as_final_exon()
final_identityscore = finalInwpCBG.get_identityscore()
final_prjtls_aadif = finalInwpCBG.get_projected_tailing_stop_aa_difference()
final_prjtls_nonad = finalInwpCBG.get_projected_tailing_stop_nonaligned_aa_difference()
# range of inwpCBGs which are checked for deletion
range_3p_test = range(posFinal+1,len(inwpcbgs))
# detect UTR or nongene / noncoding inwpCBGS
for pos in range(0,len(inwpcbgs)):
if pos not in range_3p_test: continue
# get this inwpCBG and get statistics
inwpCBG = inwpcbgs[pos]
cntFinal = inwpCBG.count_orfs_labeled_as_first_exon()
# calculated differntly as for *the* firstCBG
cntAnnot = float(inwpCBG.organism_set_size())
# break when to putatively first is reached
if cntFinal == final_cnt_is_final: break
# remove poorly covered inwpCBGs with low identityscore and not
# having a likely stop codon
if cntAnnot/max_cntAnnot < 0.80 and\
inwpCBG.get_identityscore() / final_identityscore <=\
NONCODINGNONGENE_3p_INWPCBG_MAX_IDENTITYRATIO and\
inwpCBG.organism_set_size() < final_cnt_is_final and\
final_prjtls_aadif < inwpCBG.get_projected_tailing_stop_aa_difference() and\
final_prjtls_nonad < inwpCBG.get_projected_tailing_stop_nonaligned_aa_difference():
# not contribution to the gene structure at all....
noncoding_inwpcbg_list.append(inwpCBG)
continue
# check relative position towards the current finalInwpCBG
# position is measured in actual nt distance and tcode 'distance':
# the lowest scoring TCODE window in between these inwpCBGs
ntdistdict = finalInwpCBG.nt_spacing_between_codingblocks([inwpCBG])
tcodedistdict = finalInwpCBG.tcode_spacing_between_codingblocks([inwpCBG])
# remove highest & lowest distance and then do stats on remaining dists
if len(ntdistdict) >= 3:
_tmp = [ (v,k) for k,v in ntdistdict.iteritems() ]
_tmp.sort()
del( ntdistdict[_tmp[0][1]] )
del( ntdistdict[_tmp[-1][1]] )
if len(tcodedistdict) >= 3:
_tmp = [ (v,k) for k,v in tcodedistdict.iteritems() ]
_tmp.sort()
del( tcodedistdict[_tmp[0][1]] )
del( tcodedistdict[_tmp[-1][1]] )
# do 3 checks.
# 1) are average and maximum intergenic distances are bridged?
# 2) is stop codon projection a deterioration?
# 4) does tcodedistance suggest bridging of a non-coding stretch?
check_1 = sum(ntdistdict.values())/len(ntdistdict) >=\
AVERAGE_INTERGENIC_MIN_NT_LENGTH and\
max(ntdistdict.values()) >= MAX_INTERGENIC_MIN_NT_LENGTH
check_2 = final_prjtls_aadif <\
inwpCBG.get_projected_tailing_stop_aa_difference() and\
final_prjtls_nonad <\
inwpCBG.get_projected_tailing_stop_nonaligned_aa_difference()
check_3 = len(tcodedistdict)>0 and\
sum(tcodedistdict.values())/len(tcodedistdict) <=\
TCODE_MAX_NONCODING
if [ check_1, check_2, check_3 ].count(True) >= 2:
# not contribution to the gene structure at all....
noncoding_inwpcbg_list.append(inwpCBG)
continue
# do is_coding() test
iscoding = inwpCBG.is_coding()
########################################################################
if verbose:
print pos, "3'UTR analyses:", inwpCBG, iscoding,
print cntAnnot/max_cntAnnot
########################################################################
if not iscoding:
# probably non-coding inwp CBG alignment block
noncoding_inwpcbg_list.append(inwpCBG)
continue
# return the noncoding_inwpcbg_list
return noncoding_inwpcbg_list
def assign_gtgdiscrepancy_inwpcbgs(inwpcbgs,GTG,exclude_annotated=True,verbose=True):
""" """
# return empty list when no inwpcbgs applied
if not inwpcbgs: return []
# get target organism identifier
target = inwpcbgs[0]._get_target_organism()
# return list with inwpcbgs
gtgdiscrepancy_inwpcbg_list = []
if exclude_annotated:
# get most likely first & final inwpCBG pointer in inwpcbgs list
posFirst,posFinal = get_first_and_final_inwpcbg_pos(inwpcbgs)
range_5p_test = range(0,posFirst)
range_3p_test = range(posFinal+1,len(inwpcbgs))
protected_target_orfid_list = []
for inwpCBG in inwpcbgs[posFirst:posFinal+1]:
if inwpCBG.count_orfs_labeled_as_annotated_exon() > 0:
protected_target_orfid_list.append( inwpCBG.get_orfs_of_graph(organism=target)[0].id )
else:
range_5p_test = []
range_3p_test = []
protected_target_orfid_list = []
############################################################################
if verbose and exclude_annotated:
print "NOT-excluded:", range_5p_test, range_3p_test
############################################################################
# detect UTR or nongene / noncoding inwpCBGS
for pos in range(0,len(inwpcbgs)):
if exclude_annotated and pos in range_5p_test:
pass
elif exclude_annotated and pos in range_3p_test:
pass
elif exclude_annotated and inwpcbgs[pos].count_orfs_labeled_as_annotated_exon() == 0:
# in the middle of the annotated geen structure, but not a single
# Orf annotated as an exon. Asses for gtg difference too!
pass
elif exclude_annotated:
continue
else:
pass
# get this inwpCBG and
thisInwpCBG = inwpcbgs[pos]
# ignore if the target's Orf is belonging to a `protected` Orf
if protected_target_orfid_list and\
thisInwpCBG.get_orfs_of_graph(organism=target)[0].id in\
protected_target_orfid_list:
continue
# ignore inwpCBGs which are very likely (poor quality) SignalP alignments
cntSP = float(thisInwpCBG.count_orfs_with_signalpeptides())
if cntSP/(thisInwpCBG.count_genomic_informants()+1) > 0.66 and\
thisInwpCBG.get_signalp_score() > 0.75:
continue
# create its GeneTreeGraph
gtg = pcg2gtg_by_identity(thisInwpCBG,target)
# step 1. Do the gtg/GTG difference check
difference = _relative_gtg_difference(gtg,GTG,target)
if difference < NONGENE_GTG_MAX_DIFFERENCE:
# step 2. Do the CEXPANDER check
if thisInwpCBG.node_count() <= 2:
gtgdiscrepancy_inwpcbg_list.append(thisInwpCBG)
################################################################
if verbose:
print pos, "thisInwpCBG", "gtg2GTGdiff:: %1.3f < %1.3f" % (
difference,NONGENE_GTG_MAX_DIFFERENCE),
print thisInwpCBG.get_organism_nodes(target)[0]
################################################################
elif thisInwpCBG.get_cexpander_uniformly_aligned_count() == 0:
gtgdiscrepancy_inwpcbg_list.append(thisInwpCBG)
################################################################
if verbose:
print pos, "thisInwpCBG", "gtg2GTGdiff:: %1.3f < %1.3f" % (
difference,NONGENE_GTG_MAX_DIFFERENCE),
print thisInwpCBG.get_organism_nodes(target)[0]
################################################################
else:
# cexpander check is succesfull, GTGdifference claims
# the aligment is bogus. Do a more elaborate check on
# some other variables of thisInwpCBG
# calculate the difference between minsr & maxsr lengths
node = thisInwpCBG.get_organism_nodes(target)[0]
minsr = thisInwpCBG.minimal_spanning_range_sizes()[node]
maxsr = thisInwpCBG.maximal_spanning_range_sizes()[node]
msr_ratio = float(minsr)/float(maxsr)
# calculate the ratio between average weights of gtg and GTG
average_wt_gtg = _pairwise_gtg_average_weight(gtg,target)
average_wt_GTG = _pairwise_gtg_average_weight(GTG,target)
gtg_ratio = average_wt_gtg / average_wt_GTG
if msr_ratio < NONGENE_GTG_MAX_MSR_RATIO and\
gtg_ratio < NONGENE_GTG_MAX_GTG_RATIO:
gtgdiscrepancy_inwpcbg_list.append(thisInwpCBG)
################################################################
if verbose:
print pos, "thisInwpCBG", "gtg2GTGdiff:: %1.3f < %1.3f" % (
difference,NONGENE_GTG_MAX_DIFFERENCE),
print thisInwpCBG.get_organism_nodes(target)[0]
################################################################
else:
pass
else:
pass
# return the gtgdiscrepancy_inwpcbg_list
return gtgdiscrepancy_inwpcbg_list
def assign_utrornongene5p_inwpcbgs(inwpcbgs,verbose=True):
""" """
# return empty list when no inwpcbgs applied
if not inwpcbgs: return []
# get most likely first & final inwpCBG pointer in inwpcbgs list
posFirst,posFinal = get_first_and_final_inwpcbg_pos(inwpcbgs)
# return variable list
noncoding_inwpcbg_list = []
# get data of most likely first inwpCBG
max_cntAnnot = max([inwp.count_orfs_labeled_as_annotated_exon() for inwp in inwpcbgs ])
firstInwpCBG = inwpcbgs[posFirst]
first_cnt_is_first = firstInwpCBG.count_orfs_labeled_as_first_exon()
first_identityscore = firstInwpCBG.get_identityscore()
first_upstrTSScnt = [ pf.has_upstream_tss() for pf in firstInwpCBG.pacbps.values() ].count(True)
if (max_cntAnnot-1) == 0:
# avoid ZeroDivisionError
first_upstrTSSratio = 0.0
else:
first_upstrTSSratio = float(first_upstrTSScnt) / (max_cntAnnot-1)
# range of inwpCBGs which are checked for deletion
range_5p_test = range(0,posFirst)
# detect UTR or nongene / noncoding inwpCBGS
for pos in range(0,len(inwpcbgs)):
if pos not in range_5p_test: continue
# get this inwpCBG and get statistics
inwpCBG = inwpcbgs[pos]
cntFirst = inwpCBG.count_orfs_labeled_as_first_exon()
# calculated differently as for *the* firstCBG
cntAnnot = float(inwpCBG.organism_set_size())
# break when to putatively first is reached
if cntFirst == first_cnt_is_first: break
# do is_coding() test
iscoding = inwpCBG.is_coding()
# calculate cnt/ratio of upstrTSS sites
this_upstrTSScnt = [ pf.has_upstream_tss() for pf in inwpCBG.pacbps.values() ].count(True)
if (max_cntAnnot-1) == 0:
this_upstrTSSratio = 0.0
else:
this_upstrTSSratio = float(this_upstrTSScnt) / (max_cntAnnot-1.0)
########################################################################
if verbose:
print pos, range_5p_test, "5'UTR analyses:", inwpCBG, iscoding,
print "coverage:",cntAnnot/max_cntAnnot,
print "upstrTSS cnt - ratio: %s - %1.2f" % (
this_upstrTSScnt, this_upstrTSSratio)
########################################################################
if not iscoding:
# inwpCBGs most likely not coding alignments -> remove
noncoding_inwpcbg_list.append(inwpCBG)
continue
# check relative position towards the current firstInwpCBG
# position is measured in actual nt distance and tcode 'distance':
# the lowest scoring TCODE window in between these inwpCBGs
tcodedistdict = inwpCBG.tcode_spacing_between_codingblocks([firstInwpCBG])
if len(tcodedistdict) >= 3:
_tmp = [ (v,k) for k,v in tcodedistdict.iteritems() ]
_tmp.sort()
del( tcodedistdict[_tmp[0][1]] )
del( tcodedistdict[_tmp[-1][1]] )
########################################################################
if verbose and len(tcodedistdict) >= 1:
print pos, sum(tcodedistdict.values())/len(tcodedistdict),
print TCODE_MAX_NONCODING, firstInwpCBG
########################################################################
# continue when coverage is to high
if cntAnnot/max_cntAnnot >= 0.40: continue
if len(tcodedistdict)>0 and\
sum(tcodedistdict.values())/len(tcodedistdict) <= TCODE_MAX_NONCODING:
noncoding_inwpcbg_list.append(inwpCBG)
continue
if this_upstrTSScnt == 0:
# no upstream TSS sites at all -> remove!
noncoding_inwpcbg_list.append(inwpCBG)
continue
# do a furter check for unlikely first inwpCBG blocks
if inwpCBG.get_identityscore() / first_identityscore <=\
NONCODINGNONGENE_5p_INWPCBG_MAX_IDENTITYRATIO and\
inwpCBG.organism_set_size() < first_cnt_is_first and\
first_upstrTSSratio==0.0:
noncoding_inwpcbg_list.append(inwpCBG)
continue
# do a furter check for unlikely first inwpCBG blocks
if inwpCBG.get_identityscore() / first_identityscore <=\
NONCODINGNONGENE_5p_INWPCBG_MAX_IDENTITYRATIO and\
inwpCBG.organism_set_size() < first_cnt_is_first and\
(first_upstrTSSratio!=0.0 and (this_upstrTSSratio / first_upstrTSSratio) < 0.6):
noncoding_inwpcbg_list.append(inwpCBG)
continue
# do a final check for unlikely first inwpCBG blocks
# all parameters must be (slightly) poorer
if inwpCBG.get_identityscore() < first_identityscore and\
inwpCBG.organism_set_size() < first_cnt_is_first and\
inwpCBG.get_average_upstream_methionine_pssm_score() <\
firstInwpCBG.get_average_upstream_methionine_pssm_score():
noncoding_inwpcbg_list.append(inwpCBG)
continue
# return the noncoding_inwpcbg_list
return noncoding_inwpcbg_list
def assign_internal_nongene_alignments(inwpcbgs,GTG,exclude_annotated=False,verbose=True):
"""
TODO TODO: this function must be moved to another location.
TODO TODO: better place in inwpCBGs/blocks filtering
"""
# return empty list when no inwpcbgs applied
if not inwpcbgs: return []
# get target organism identifier
target = inwpcbgs[0]._get_target_organism()
# return list with inwpcbgs
gtgdiscrepancy_inwpcbg_list = []
# get most likely first & final inwpCBG pointer in inwpcbgs list
posFirst,posFinal = get_first_and_final_inwpcbg_pos(inwpcbgs)
# check if posFirst,posFinal+1 isa non-empty range
if not range(posFirst,posFinal+1): return []
# get info on the *best* covered inwpCBG
best_nt_identity = max([ inwpcbgs[pos].get_nt_identity() for pos in range(posFirst,posFinal+1) ])
best_bitscore = max([ inwpcbgs[pos].get_bitscore() for pos in range(posFirst,posFinal+1) ])
best_annot_cnt = max([ inwpcbgs[pos].count_orfs_labeled_as_annotated_exon() for pos in range(posFirst,posFinal+1) ])
best_bits_per_aa = max([ float( inwpcbgs[pos].get_bitscore() ) / float( sum([pf.get_unextended_length() for pf in inwpcbgs[pos].pacbps.values() ]) ) for pos in range(posFirst,posFinal+1) ])
for pos in range(posFirst,posFinal+1):
# get this inwpCBG and
thisInwpCBG = inwpcbgs[pos]
if pos > 0: prevInwpCBG = inwpcbgs[pos-1]
else: prevInwpCBG = None
if pos < len(inwpcbgs)-1: nextInwpCBG = inwpcbgs[pos+1]
else: nextInwpCBG = None
if prevInwpCBG and Set(prevInwpCBG.get_nodes()).intersection(thisInwpCBG.get_nodes()):
continue
if nextInwpCBG and Set(nextInwpCBG.get_nodes()).intersection(thisInwpCBG.get_nodes()):
continue
tot_length = sum([pf.get_unextended_length() for pf in thisInwpCBG.pacbps.values() ])
bits = thisInwpCBG.get_bitscore()
bits_per_aa = float(bits)/float(tot_length)
if bits_per_aa/best_bits_per_aa < 0.55 and\
float(thisInwpCBG.count_orfs_labeled_as_annotated_exon()) /\
float(best_annot_cnt) <= 0.50:
minsr = thisInwpCBG.minimal_spanning_range(organism=target)
print " __XX__", pos, thisInwpCBG, thisInwpCBG.get_nt_identity(), bits, float(bits)/float(tot_length), thisInwpCBG.count_orfs_labeled_as_annotated_exon()
if prevInwpCBG and len(prevInwpCBG.maximal_spanning_range(organism=target).intersection(minsr)) == len(minsr):
################################################################
if verbose:
print "PREV::", len(prevInwpCBG.maximal_spanning_range(organism=target).intersection(minsr)), len(minsr)
################################################################
gtgdiscrepancy_inwpcbg_list.append( thisInwpCBG )
continue
if nextInwpCBG and len(nextInwpCBG.maximal_spanning_range(organism=target).intersection(minsr)) == len(minsr):
################################################################
if verbose:
print "NEXT::", len(nextInwpCBG.maximal_spanning_range(organism=target).intersection(minsr)), len(minsr)
################################################################
gtgdiscrepancy_inwpcbg_list.append( thisInwpCBG )
continue
# return list with conflicts
return gtgdiscrepancy_inwpcbg_list
def assign_utrornongene3p_inwpcbgs(inwpcbgs, verbose=True):
""" """
# return empty list when no inwpcbgs applied
if not inwpcbgs: return []
# get most likely first & final inwpCBG pointer in inwpcbgs list
posFirst, posFinal = get_first_and_final_inwpcbg_pos(inwpcbgs)
# return variable list
noncoding_inwpcbg_list = []
# get data of most likely first inwpCBG
max_cntAnnot = max(
[inwp.count_orfs_labeled_as_annotated_exon() for inwp in inwpcbgs])
finalInwpCBG = inwpcbgs[posFinal]
final_cnt_is_final = finalInwpCBG.count_orfs_labeled_as_final_exon()
final_identityscore = finalInwpCBG.get_identityscore()
final_prjtls_aadif = finalInwpCBG.get_projected_tailing_stop_aa_difference(
)
final_prjtls_nonad = finalInwpCBG.get_projected_tailing_stop_nonaligned_aa_difference(
)
# range of inwpCBGs which are checked for deletion
range_3p_test = range(posFinal + 1, len(inwpcbgs))
# detect UTR or nongene / noncoding inwpCBGS
for pos in range(0, len(inwpcbgs)):
if pos not in range_3p_test: continue
# get this inwpCBG and get statistics
inwpCBG = inwpcbgs[pos]
cntFinal = inwpCBG.count_orfs_labeled_as_first_exon()
# calculated differntly as for *the* firstCBG
cntAnnot = float(inwpCBG.organism_set_size())
# break when to putatively first is reached
if cntFinal == final_cnt_is_final: break
# remove poorly covered inwpCBGs with low identityscore and not
# having a likely stop codon
if cntAnnot/max_cntAnnot < 0.80 and\
inwpCBG.get_identityscore() / final_identityscore <=\
NONCODINGNONGENE_3p_INWPCBG_MAX_IDENTITYRATIO and\
inwpCBG.organism_set_size() < final_cnt_is_final and\
final_prjtls_aadif < inwpCBG.get_projected_tailing_stop_aa_difference() and\
final_prjtls_nonad < inwpCBG.get_projected_tailing_stop_nonaligned_aa_difference():
# not contribution to the gene structure at all....
noncoding_inwpcbg_list.append(inwpCBG)
continue
# check relative position towards the current finalInwpCBG
# position is measured in actual nt distance and tcode 'distance':
# the lowest scoring TCODE window in between these inwpCBGs
ntdistdict = finalInwpCBG.nt_spacing_between_codingblocks([inwpCBG])
tcodedistdict = finalInwpCBG.tcode_spacing_between_codingblocks(
[inwpCBG])
# remove highest & lowest distance and then do stats on remaining dists
if len(ntdistdict) >= 3:
_tmp = [(v, k) for k, v in ntdistdict.iteritems()]
_tmp.sort()
del (ntdistdict[_tmp[0][1]])
del (ntdistdict[_tmp[-1][1]])
if len(tcodedistdict) >= 3:
_tmp = [(v, k) for k, v in tcodedistdict.iteritems()]
_tmp.sort()
del (tcodedistdict[_tmp[0][1]])
del (tcodedistdict[_tmp[-1][1]])
# do 3 checks.
# 1) are average and maximum intergenic distances are bridged?
# 2) is stop codon projection a deterioration?
# 4) does tcodedistance suggest bridging of a non-coding stretch?
check_1 = sum(ntdistdict.values())/len(ntdistdict) >=\
AVERAGE_INTERGENIC_MIN_NT_LENGTH and\
max(ntdistdict.values()) >= MAX_INTERGENIC_MIN_NT_LENGTH
check_2 = final_prjtls_aadif <\
inwpCBG.get_projected_tailing_stop_aa_difference() and\
final_prjtls_nonad <\
inwpCBG.get_projected_tailing_stop_nonaligned_aa_difference()
check_3 = len(tcodedistdict)>0 and\
sum(tcodedistdict.values())/len(tcodedistdict) <=\
TCODE_MAX_NONCODING
if [check_1, check_2, check_3].count(True) >= 2:
# not contribution to the gene structure at all....
noncoding_inwpcbg_list.append(inwpCBG)
continue
# do is_coding() test
iscoding = inwpCBG.is_coding()
########################################################################
if verbose:
print pos, "3'UTR analyses:", inwpCBG, iscoding,
print cntAnnot / max_cntAnnot
########################################################################
if not iscoding:
# probably non-coding inwp CBG alignment block
noncoding_inwpcbg_list.append(inwpCBG)
continue
# return the noncoding_inwpcbg_list
return noncoding_inwpcbg_list
def assign_utrornongene5p_inwpcbgs(inwpcbgs, verbose=True):
""" """
# return empty list when no inwpcbgs applied
if not inwpcbgs: return []
# get most likely first & final inwpCBG pointer in inwpcbgs list
posFirst, posFinal = get_first_and_final_inwpcbg_pos(inwpcbgs)
# return variable list
noncoding_inwpcbg_list = []
# get data of most likely first inwpCBG
max_cntAnnot = max(
[inwp.count_orfs_labeled_as_annotated_exon() for inwp in inwpcbgs])
firstInwpCBG = inwpcbgs[posFirst]
first_cnt_is_first = firstInwpCBG.count_orfs_labeled_as_first_exon()
first_identityscore = firstInwpCBG.get_identityscore()
first_upstrTSScnt = [
pf.has_upstream_tss() for pf in firstInwpCBG.pacbps.values()
].count(True)
if (max_cntAnnot - 1) == 0:
# avoid ZeroDivisionError
first_upstrTSSratio = 0.0
else:
first_upstrTSSratio = float(first_upstrTSScnt) / (max_cntAnnot - 1)
# range of inwpCBGs which are checked for deletion
range_5p_test = range(0, posFirst)
# detect UTR or nongene / noncoding inwpCBGS
for pos in range(0, len(inwpcbgs)):
if pos not in range_5p_test: continue
# get this inwpCBG and get statistics
inwpCBG = inwpcbgs[pos]
cntFirst = inwpCBG.count_orfs_labeled_as_first_exon()
# calculated differently as for *the* firstCBG
cntAnnot = float(inwpCBG.organism_set_size())
# break when to putatively first is reached
if cntFirst == first_cnt_is_first: break
# do is_coding() test
iscoding = inwpCBG.is_coding()
# calculate cnt/ratio of upstrTSS sites
this_upstrTSScnt = [
pf.has_upstream_tss() for pf in inwpCBG.pacbps.values()
].count(True)
if (max_cntAnnot - 1) == 0:
this_upstrTSSratio = 0.0
else:
this_upstrTSSratio = float(this_upstrTSScnt) / (max_cntAnnot - 1.0)
########################################################################
if verbose:
print pos, range_5p_test, "5'UTR analyses:", inwpCBG, iscoding,
print "coverage:", cntAnnot / max_cntAnnot,
print "upstrTSS cnt - ratio: %s - %1.2f" % (this_upstrTSScnt,
this_upstrTSSratio)
########################################################################
if not iscoding:
# inwpCBGs most likely not coding alignments -> remove
noncoding_inwpcbg_list.append(inwpCBG)
continue
# check relative position towards the current firstInwpCBG
# position is measured in actual nt distance and tcode 'distance':
# the lowest scoring TCODE window in between these inwpCBGs
tcodedistdict = inwpCBG.tcode_spacing_between_codingblocks(
[firstInwpCBG])
if len(tcodedistdict) >= 3:
_tmp = [(v, k) for k, v in tcodedistdict.iteritems()]
_tmp.sort()
del (tcodedistdict[_tmp[0][1]])
del (tcodedistdict[_tmp[-1][1]])
########################################################################
if verbose and len(tcodedistdict) >= 1:
print pos, sum(tcodedistdict.values()) / len(tcodedistdict),
print TCODE_MAX_NONCODING, firstInwpCBG
########################################################################
# continue when coverage is to high
if cntAnnot / max_cntAnnot >= 0.40: continue
if len(tcodedistdict)>0 and\
sum(tcodedistdict.values())/len(tcodedistdict) <= TCODE_MAX_NONCODING:
noncoding_inwpcbg_list.append(inwpCBG)
continue
if this_upstrTSScnt == 0:
# no upstream TSS sites at all -> remove!
noncoding_inwpcbg_list.append(inwpCBG)
continue
# do a furter check for unlikely first inwpCBG blocks
if inwpCBG.get_identityscore() / first_identityscore <=\
NONCODINGNONGENE_5p_INWPCBG_MAX_IDENTITYRATIO and\
inwpCBG.organism_set_size() < first_cnt_is_first and\
first_upstrTSSratio==0.0:
noncoding_inwpcbg_list.append(inwpCBG)
continue
# do a furter check for unlikely first inwpCBG blocks
if inwpCBG.get_identityscore() / first_identityscore <=\
NONCODINGNONGENE_5p_INWPCBG_MAX_IDENTITYRATIO and\
inwpCBG.organism_set_size() < first_cnt_is_first and\
(first_upstrTSSratio!=0.0 and (this_upstrTSSratio / first_upstrTSSratio) < 0.6):
noncoding_inwpcbg_list.append(inwpCBG)
continue
# do a final check for unlikely first inwpCBG blocks
# all parameters must be (slightly) poorer
if inwpCBG.get_identityscore() < first_identityscore and\
inwpCBG.organism_set_size() < first_cnt_is_first and\
inwpCBG.get_average_upstream_methionine_pssm_score() <\
firstInwpCBG.get_average_upstream_methionine_pssm_score():
noncoding_inwpcbg_list.append(inwpCBG)
continue
# return the noncoding_inwpcbg_list
return noncoding_inwpcbg_list
def assign_gtgdiscrepancy_inwpcbgs(inwpcbgs,
GTG,
exclude_annotated=True,
verbose=True):
""" """
# return empty list when no inwpcbgs applied
if not inwpcbgs: return []
# get target organism identifier
target = inwpcbgs[0]._get_target_organism()
# return list with inwpcbgs
gtgdiscrepancy_inwpcbg_list = []
if exclude_annotated:
# get most likely first & final inwpCBG pointer in inwpcbgs list
posFirst, posFinal = get_first_and_final_inwpcbg_pos(inwpcbgs)
range_5p_test = range(0, posFirst)
range_3p_test = range(posFinal + 1, len(inwpcbgs))
protected_target_orfid_list = []
for inwpCBG in inwpcbgs[posFirst:posFinal + 1]:
if inwpCBG.count_orfs_labeled_as_annotated_exon() > 0:
protected_target_orfid_list.append(
inwpCBG.get_orfs_of_graph(organism=target)[0].id)
else:
range_5p_test = []
range_3p_test = []
protected_target_orfid_list = []
############################################################################
if verbose and exclude_annotated:
print "NOT-excluded:", range_5p_test, range_3p_test
############################################################################
# detect UTR or nongene / noncoding inwpCBGS
for pos in range(0, len(inwpcbgs)):
if exclude_annotated and pos in range_5p_test:
pass
elif exclude_annotated and pos in range_3p_test:
pass
elif exclude_annotated and inwpcbgs[
pos].count_orfs_labeled_as_annotated_exon() == 0:
# in the middle of the annotated geen structure, but not a single
# Orf annotated as an exon. Asses for gtg difference too!
pass
elif exclude_annotated:
continue
else:
pass
# get this inwpCBG and
thisInwpCBG = inwpcbgs[pos]
# ignore if the target's Orf is belonging to a `protected` Orf
if protected_target_orfid_list and\
thisInwpCBG.get_orfs_of_graph(organism=target)[0].id in\
protected_target_orfid_list:
continue
# ignore inwpCBGs which are very likely (poor quality) SignalP alignments
cntSP = float(thisInwpCBG.count_orfs_with_signalpeptides())
if cntSP/(thisInwpCBG.count_genomic_informants()+1) > 0.66 and\
thisInwpCBG.get_signalp_score() > 0.75:
continue
# create its GeneTreeGraph
gtg = pcg2gtg_by_identity(thisInwpCBG, target)
# step 1. Do the gtg/GTG difference check
difference = _relative_gtg_difference(gtg, GTG, target)
if difference < NONGENE_GTG_MAX_DIFFERENCE:
# step 2. Do the CEXPANDER check
if thisInwpCBG.node_count() <= 2:
gtgdiscrepancy_inwpcbg_list.append(thisInwpCBG)
################################################################
if verbose:
print pos, "thisInwpCBG", "gtg2GTGdiff:: %1.3f < %1.3f" % (
difference, NONGENE_GTG_MAX_DIFFERENCE),
print thisInwpCBG.get_organism_nodes(target)[0]
################################################################
elif thisInwpCBG.get_cexpander_uniformly_aligned_count() == 0:
gtgdiscrepancy_inwpcbg_list.append(thisInwpCBG)
################################################################
if verbose:
print pos, "thisInwpCBG", "gtg2GTGdiff:: %1.3f < %1.3f" % (
difference, NONGENE_GTG_MAX_DIFFERENCE),
print thisInwpCBG.get_organism_nodes(target)[0]
################################################################
else:
# cexpander check is succesfull, GTGdifference claims
# the aligment is bogus. Do a more elaborate check on
# some other variables of thisInwpCBG
# calculate the difference between minsr & maxsr lengths
node = thisInwpCBG.get_organism_nodes(target)[0]
minsr = thisInwpCBG.minimal_spanning_range_sizes()[node]
maxsr = thisInwpCBG.maximal_spanning_range_sizes()[node]
msr_ratio = float(minsr) / float(maxsr)
# calculate the ratio between average weights of gtg and GTG
average_wt_gtg = _pairwise_gtg_average_weight(gtg, target)
average_wt_GTG = _pairwise_gtg_average_weight(GTG, target)
gtg_ratio = average_wt_gtg / average_wt_GTG
if msr_ratio < NONGENE_GTG_MAX_MSR_RATIO and\
gtg_ratio < NONGENE_GTG_MAX_GTG_RATIO:
gtgdiscrepancy_inwpcbg_list.append(thisInwpCBG)
################################################################
if verbose:
print pos, "thisInwpCBG", "gtg2GTGdiff:: %1.3f < %1.3f" % (
difference, NONGENE_GTG_MAX_DIFFERENCE),
print thisInwpCBG.get_organism_nodes(target)[0]
################################################################
else:
pass
else:
pass
# return the gtgdiscrepancy_inwpcbg_list
return gtgdiscrepancy_inwpcbg_list
def assign_internal_nongene_alignments(inwpcbgs,
GTG,
exclude_annotated=False,
verbose=True):
"""
TODO TODO: this function must be moved to another location.
TODO TODO: better place in inwpCBGs/blocks filtering
"""
# return empty list when no inwpcbgs applied
if not inwpcbgs: return []
# get target organism identifier
target = inwpcbgs[0]._get_target_organism()
# return list with inwpcbgs
gtgdiscrepancy_inwpcbg_list = []
# get most likely first & final inwpCBG pointer in inwpcbgs list
posFirst, posFinal = get_first_and_final_inwpcbg_pos(inwpcbgs)
# check if posFirst,posFinal+1 isa non-empty range
if not range(posFirst, posFinal + 1): return []
# get info on the *best* covered inwpCBG
best_nt_identity = max([
inwpcbgs[pos].get_nt_identity()
for pos in range(posFirst, posFinal + 1)
])
best_bitscore = max([
inwpcbgs[pos].get_bitscore() for pos in range(posFirst, posFinal + 1)
])
best_annot_cnt = max([
inwpcbgs[pos].count_orfs_labeled_as_annotated_exon()
for pos in range(posFirst, posFinal + 1)
])
best_bits_per_aa = max([
float(inwpcbgs[pos].get_bitscore()) / float(
sum([
pf.get_unextended_length()
for pf in inwpcbgs[pos].pacbps.values()
])) for pos in range(posFirst, posFinal + 1)
])
for pos in range(posFirst, posFinal + 1):
# get this inwpCBG and
thisInwpCBG = inwpcbgs[pos]
if pos > 0: prevInwpCBG = inwpcbgs[pos - 1]
else: prevInwpCBG = None
if pos < len(inwpcbgs) - 1: nextInwpCBG = inwpcbgs[pos + 1]
else: nextInwpCBG = None
if prevInwpCBG and Set(prevInwpCBG.get_nodes()).intersection(
thisInwpCBG.get_nodes()):
continue
if nextInwpCBG and Set(nextInwpCBG.get_nodes()).intersection(
thisInwpCBG.get_nodes()):
continue
tot_length = sum(
[pf.get_unextended_length() for pf in thisInwpCBG.pacbps.values()])
bits = thisInwpCBG.get_bitscore()
bits_per_aa = float(bits) / float(tot_length)
if bits_per_aa/best_bits_per_aa < 0.55 and\
float(thisInwpCBG.count_orfs_labeled_as_annotated_exon()) /\
float(best_annot_cnt) <= 0.50:
minsr = thisInwpCBG.minimal_spanning_range(organism=target)
print " __XX__", pos, thisInwpCBG, thisInwpCBG.get_nt_identity(
), bits, float(bits) / float(
tot_length), thisInwpCBG.count_orfs_labeled_as_annotated_exon(
)
if prevInwpCBG and len(
prevInwpCBG.maximal_spanning_range(
organism=target).intersection(minsr)) == len(minsr):
################################################################
if verbose:
print "PREV::", len(
prevInwpCBG.maximal_spanning_range(
organism=target).intersection(minsr)), len(minsr)
################################################################
gtgdiscrepancy_inwpcbg_list.append(thisInwpCBG)
continue
if nextInwpCBG and len(
nextInwpCBG.maximal_spanning_range(
organism=target).intersection(minsr)) == len(minsr):
################################################################
if verbose:
print "NEXT::", len(
nextInwpCBG.maximal_spanning_range(
organism=target).intersection(minsr)), len(minsr)
################################################################
gtgdiscrepancy_inwpcbg_list.append(thisInwpCBG)
continue
# return list with conflicts
return gtgdiscrepancy_inwpcbg_list
