def print_stuff(line):
cluster_index = sorted_clusters.index(cluster)
naive_cdr3, matureiseq0_cdr3 = utils.subset_sequences(
line, iseq=0, restrict_to_region='cdr3'
) # line['naive_seq'][(line['codon_positions']['v']):((line['codon_positions']['j'])+3)] #get nt sequence of CDR3 from first base of cysteine through last base of tryptophan
# mature_cdr3_seqs = [] # trying to translate the consensus cdr3 so I can search these with my seed seqs
# for iseq in range(len(line['unique_ids'])):
# naive_cdr3_seq, mature_cdr3_seq = utils.subset_sequences(line, iseq=iseq, restrict_to_region='cdr3')
# mature_cdr3_seqs.append(mature_cdr3_seq)
# translated_cdr3 = Seq().... not done
cdr3_aa = '%-30s' % Seq(naive_cdr3).translate()
if any('-ig' in s for s in line['unique_ids']):
cdr3_aa = utils.color('red', cdr3_aa, width=30)
print '%4s %s %s %s %5d %5d %5d %7.3f %8.4f %2d %s %4.2f' % (
cluster_index,
utils.color_gene(line['v_gene'], width=15),
utils.color_gene(line['d_gene'], width=15),
utils.color_gene(line['j_gene'], width=10),
len(line['unique_ids']),
numpy.mean(line['n_mutations']),
numpy.median(line['n_mutations']),
numpy.mean(line['mut_freqs']),
float(len(cluster)) / n_total,
(line['cdr3_length'] / 3),
cdr3_aa,
utils.fay_wu_h(line, debug=False),
)
def get_cdr3_title(self, annotation):
naive_cdr3_seq, _ = utils.subset_sequences(annotation,
iseq=0,
restrict_to_region='cdr3')
title = ''
if len(naive_cdr3_seq) % 3 != 0:
# print ' out of frame: adding %s' % ((3 - len(naive_cdr3_seq) % 3) * 'N')
naive_cdr3_seq += (3 - len(naive_cdr3_seq) % 3) * 'N'
title += ' (out of frame)'
title = self.Seq.Seq(naive_cdr3_seq).translate() + title
return title
def print_stuff(line):
cluster_index = sorted_clusters.index(cluster)
naive_cdr3, matureiseq0_cdr3 = utils.subset_sequences(line, iseq=0, restrict_to_region='cdr3') # returns the CDR3 nt sequence for naive, and the first mutated sequence (iseq0); CDR3 = first base of cysteine through last base of tryptophan
# mature_cdr3_seqs = [] # trying to translate the consensus cdr3 so I can search these with my seed seqs
# for iseq in range(len(line['unique_ids'])):
# naive_cdr3_seq, mature_cdr3_seq = utils.subset_sequences(line, iseq=iseq, restrict_to_region='cdr3')
# mature_cdr3_seqs.append(mature_cdr3_seq)
# mature_cdr3_seqs
# translated_cdr3 = mature_cdr3_seqs.translate()
cdr3_aa = '%-30s' % Seq(naive_cdr3).translate()
# If a cluster contains one of our seed seqs, color this CDR3 red
if any('-ig' in s for s in line['unique_ids']):
cdr3_aa = utils.color('red', cdr3_aa, width=30)
if args.cdr3 in cdr3_aa: # Only print clusters with naive CDR3 that matches our specified --cdr3 argument
print 'index genes size n muts SHM rep frac CDR3 FayWuH'
print ' mean med len seq'
print '%4s %s %s %s %5d %5d %5d %7.3f %8.4f %2d %s %4.2f' % (
cluster_index,
utils.color_gene(line['v_gene'], width=15),
utils.color_gene(line['d_gene'], width=15),
utils.color_gene(line['j_gene'], width=10),
len(line['unique_ids']),
numpy.mean(line['n_mutations']),
numpy.median(line['n_mutations']),
numpy.mean(line['mut_freqs']),
float(len(cluster)) / n_total,
(line['cdr3_length']/3),
cdr3_aa,
utils.fay_wu_h(line, debug=False),
)
# print 'number of mutations per sequence in cluster', sorted(line['n_mutations'])
print len(line['naive_seq']), 'length of naive seq'
# utils.print_reco_event(utils.synthesize_single_seq_line(line, iseq=0)) # print ascii-art representation of the rearrangement event
print 'unique_ids: ', getkey(line['unique_ids'])
print
print utils.print_reco_event(line)
def naive_cdr3(info):
naiveseq, _ = utils.subset_sequences(info,
iseq=0,
restrict_to_region='cdr3')
return naiveseq
def print_stuff(line):
intscore = 0 # create a clonal family scoring system
cluster_index = sorted_clusters.index(cluster)
shm_index = shm_clusters.index(cluster)
naive_cdr3, matureiseq0_cdr3 = utils.subset_sequences(
line, iseq=0, restrict_to_region='cdr3'
) # line['naive_seq'][(line['codon_positions']['v']):((line['codon_positions']['j'])+3)] #get nt sequence of CDR3 from first base of cysteine through last base of tryptophan
# mature_cdr3_seqs = [] # trying to translate the consensus cdr3 so I can search these with my seed seqs
# for iseq in range(len(line['unique_ids'])):
# naive_cdr3_seq, mature_cdr3_seq = utils.subset_sequences(line, iseq=iseq, restrict_to_region='cdr3')
# mature_cdr3_seqs.append(mature_cdr3_seq)
# translated_cdr3 = Seq().... not done
cdr3_aa = '%-30s' % Seq(naive_cdr3).translate()
if any('-ig' in s for s in line['unique_ids']):
cdr3_aa = utils.color('red', cdr3_aa, width=30)
# score clusters based on cluster size
if cluster_index < 25:
intscore = intscore + 4
elif cluster_index >= 25 and cluster_index <= 50:
intscore = intscore + 3
elif cluster_index >= 50 and cluster_index <= 75:
intscore = intscore + 2
elif cluster_index >= 75 and cluster_index <= 100:
intscore = intscore + 1
# score clusters based on SHM
if shm_index < 25:
intscore = intscore + 4
elif shm_index >= 25 and shm_index <= 50:
intscore = intscore + 3
elif shm_index >= 50 and shm_index <= 75:
intscore = intscore + 2
elif shm_index >= 75 and shm_index <= 100:
intscore = intscore + 1
# score clusters based on SFS
if utils.fay_wu_h(line, debug=False) <= -20:
intscore = intscore + 4
elif utils.fay_wu_h(line, debug=False) <= -10:
intscore = intscore + 3
elif utils.fay_wu_h(line, debug=False) <= 0:
intscore = intscore + 2
elif utils.fay_wu_h(line, debug=False) <= 10:
intscore = intscore + 1
# score by bnAb gene usage
if (line['v_gene']).split('*')[0] in (
cd4bs_genes or glycan_genes or bridging_genes or mper_genes
): # beware this does not include CDR3 length of bnAb VH genes
intscore = intscore + 4
print '%4s %4s %s %s %s %5d %5d %5d %7.3f %8.4f %2d %s %4.2f' % (
intscore,
cluster_index,
utils.color_gene(line['v_gene'], width=15),
utils.color_gene(line['d_gene'], width=15),
utils.color_gene(line['j_gene'], width=10),
len(line['unique_ids']),
numpy.mean(line['n_mutations']),
numpy.median(line['n_mutations']),
numpy.mean(line['mut_freqs']),
float(len(cluster)) / n_total,
(line['cdr3_length'] / 3),
cdr3_aa,
utils.fay_wu_h(line, debug=False),
)