def get_v_cdr3_nucseq( organism, v_gene, paranoid = False ):
ab = v_gene[2]
v_nucseq = read_sanger_data.all_fasta[organism][ab]['V'][read_sanger_data.nuc ][v_gene]
v_nucseq_offset = read_sanger_data.all_offsets[organism][ab]['V'][v_gene]
v_nucseq = v_nucseq[ v_nucseq_offset: ]
if paranoid:
v_protseq = read_sanger_data.all_fasta[organism][ab]['V'][read_sanger_data.prot][v_gene]
assert read_sanger_data.get_translation( v_nucseq, '+1' )[0].startswith( v_protseq )
v_alseq = cdr3s_human.all_align_fasta[organism][ v_gene ]
alseq_cpos = cdr3s_human.alseq_C_pos[organism][ab]-1 ## 0-indexed
numgaps = v_alseq[:alseq_cpos].count('.')
v_cpos = alseq_cpos - numgaps
v_nucseq = v_nucseq[3*v_cpos:] ## now v_nucseq starts with the 'C' codon
if organism == 'mouse':
if v_gene == 'TRAV13D-1*01':
#-----------------------------------
#../../../tmp.blat:mismatch: V 6 imgt: a genome: t TRAV13D-1*01
#tmp.whoah:whoah 6 act: t 98.7 exp: a 1.1 TRAV13D-1*01 TRAV13-1*01 620
#tmp.whoah:whoah: expected: caaggtatcgtgt consensus: caaggtttcgtgt TRAV13D-1*01 620
#tmp.3.whoah:whoah 6 act: t 97.4 exp: a 1.4 TRAV13D-1*01 TRAV13-1*01 642
#tmp.3.whoah:whoah: expected: caaggtatcgtgt consensus: caaggtttcgtgt TRAV13D-1*01 642
#tmp.la_mc.whoah:whoah 6 act: t 89.0 exp: a 7.0 TRAV13D-1*01 TRAV13-1*01 100
#tmp.la_mc.whoah:whoah: expected: caaggtatcgtgt consensus: caaggtttcgtgt TRAV13D-1*01 100
assert v_nucseq == 'tgtgctatggaac' ## CAM
v_nucseq = 'tgtgctttggaac' ## CAL
return v_nucseq
def get_j_cdr3_nucseq( organism, j_gene, paranoid = False ):
ab = j_gene[2]
j_nucseq = read_sanger_data.all_fasta[organism][ab]['J'][read_sanger_data.nuc ][j_gene]
j_nucseq_offset = read_sanger_data.all_offsets[organism][ab]['J'][j_gene]
if paranoid:
j_protseq = read_sanger_data.all_fasta[organism][ab]['J'][read_sanger_data.prot][j_gene]
assert read_sanger_data.get_translation( j_nucseq, '+{}'.format(j_nucseq_offset+1) )[0].startswith( j_protseq )
num_genome_j_positions_in_loop = cdr3s_human.all_num_genome_j_positions_in_loop[organism][ab][j_gene] + 2 ## to GXG
## trim j_nucseq so that it extends up to the F/W position
j_nucseq = j_nucseq[:3*num_genome_j_positions_in_loop + j_nucseq_offset]
if organism == 'mouse':
if j_gene == 'TRAJ47*01':
# -----------------------------------
# ../../../tmp.blat:mismatch: J 2 imgt: c genome: g TRAJ47*01
# ../../../tmp.blat:mismatch: J 24 imgt: g genome: t TRAJ47*01
# tmp.whoah:whoah 2 act: g 81.9 exp: c 4.7 TRAJ47*01 TRAJ47*01 1412
# tmp.whoah:whoah 24 act: t 82.7 exp: g 16.8 TRAJ47*01 TRAJ47*01 1412
# tmp.whoah:whoah: expected: tgcactatgcaaacaagatgatctgt consensus: tggactatgcaaacaagatgatcttt TRAJ47*01 1412
# tmp.3.whoah:whoah 2 act: g 81.6 exp: c 5.0 TRAJ47*01 TRAJ47*01 1362
# tmp.3.whoah:whoah 24 act: t 82.7 exp: g 16.6 TRAJ47*01 TRAJ47*01 1362
# tmp.3.whoah:whoah: expected: tgcactatgcaaacaagatgatctgt consensus: tggactatgcaaacaagatgatcttt TRAJ47*01 1362
# tmp.la_mc.whoah:whoah 2 act: g 79.6 exp: c 5.3 TRAJ47*01 TRAJ47*01 113
# tmp.la_mc.whoah:whoah 24 act: t 99.1 exp: g 0.9 TRAJ47*01 TRAJ47*01 113
# tmp.la_mc.whoah:whoah: expected: tgcactatgcaaacaagatgatctgt consensus: tggactatgcaaacaagatgatcttt TRAJ47*01 113
assert j_nucseq == 'tgcactatgcaaacaagatgatctgt' ## C at end
j_nucseq = 'tggactatgcaaacaagatgatcttt' ## F at end
elif j_gene == 'TRAJ24*01':
# -----------------------------------
# ../../../tmp.blat:unaligned: J 0 TRAJ24*01
# ../../../tmp.blat:unaligned: J 1 TRAJ24*01
# ../../../tmp.blat:gapped: J 6 TRAJ24*01
# tmp.whoah:whoah 2 act: c 60.3 exp: a 15.3 TRAJ24*01 TRAJ24*01 464
# tmp.whoah:whoah 4 act: a 88.6 exp: c 2.8 TRAJ24*01 TRAJ24*01 464
# tmp.whoah:whoah 5 act: c 93.3 exp: t 1.5 TRAJ24*01 TRAJ24*01 464
# tmp.whoah:whoah 6 act: t 97.2 exp: g 1.1 TRAJ24*01 TRAJ24*01 464
# tmp.whoah:whoah: expected: tgaactggccagtttggggaaactgcagttt consensus: gacaactgccagtttggggaaactgcagttt TRAJ24*01 464
# tmp.3.whoah:whoah 2 act: c 60.8 exp: a 13.9 TRAJ24*01 TRAJ24*01 475
# tmp.3.whoah:whoah 4 act: a 86.3 exp: c 4.2 TRAJ24*01 TRAJ24*01 475
# tmp.3.whoah:whoah 5 act: c 94.5 exp: t 1.1 TRAJ24*01 TRAJ24*01 475
# tmp.3.whoah:whoah 6 act: t 98.1 exp: g 1.1 TRAJ24*01 TRAJ24*01 475
# tmp.3.whoah:whoah: expected: tgaactggccagtttggggaaactgcagttt consensus: gacaactgccagtttggggaaactgcagttt TRAJ24*01 475
# tmp.la_mc.whoah:whoah 2 act: c 75.3 exp: a 4.3 TRAJ24*01 TRAJ24*01 93
# tmp.la_mc.whoah:whoah 4 act: a 89.2 exp: c 2.2 TRAJ24*01 TRAJ24*01 93
# tmp.la_mc.whoah:whoah 5 act: c 97.8 exp: t 1.1 TRAJ24*01 TRAJ24*01 93
# tmp.la_mc.whoah:whoah 6 act: t 98.9 exp: g 0.0 TRAJ24*01 TRAJ24*01 93
# tmp.la_mc.whoah:whoah: expected: tgaactggccagtttggggaaactgcagttt consensus: gacaactgccagtttggggaaactgcagttt TRAJ24*01 93
assert j_nucseq == 'tgaactggccagtttggggaaactgcagttt'
j_nucseq = 'gacaactgccagtttggggaaactgcagttt'
## take the consensus
## given that there's an indel (and the alignment to the genome starts at j sequence position 3)
## it's hard to tell what to do at the beginning...
return j_nucseq
Log('skipping: badseq: {} {}'.format(
cdr3a_protseq, cdr3b_protseq))
skip_me = True
break
if skip_me:
continue
## probs are computed by reps
va_reps = l['va_reps'].split(';')
ja_reps = l['ja_reps'].split(';')
va_countreps = l['va_countreps'].split(';')
ja_countreps = l['ja_countreps'].split(';')
va_cdr3_nucseq = tcr_sampler.get_v_cdr3_nucseq(organism, va_gene)
ja_cdr3_nucseq = tcr_sampler.get_j_cdr3_nucseq(organism, ja_gene)
va_cdr3_protseq, codons = read_sanger_data.get_translation(
va_cdr3_nucseq, '+1')
ja_cdr3_protseq, codons = read_sanger_data.get_translation(
ja_cdr3_nucseq, '+{}'.format(1 + len(ja_cdr3_nucseq) % 3))
aprob_nucseq, new_cdr3a_nucseq = tcr_sampler.alpha_cdr3_protseq_probability(
organism,
va_gene,
ja_gene,
cdr3_protseq='',
cdr3_nucseq=cdr3a_nucseq,
verbose=verbose,
return_final_cdr3_nucseq=True)
if new_cdr3a_nucseq != cdr3a_nucseq: ## note note note
print 'new_cdr3a_nucseq:', len(new_cdr3a_nucseq), new_cdr3a_nucseq
print 'old_cdr3a_nucseq:', len(cdr3a_nucseq), cdr3a_nucseq
def beta_cdr3_protseq_probability( organism, v_gene, j_gene, cdr3_protseq,
cdr3_nucseq = '', error_threshold = 0.05, verbose=False,
allow_early_nucseq_mismatches = True,
return_final_cdr3_nucseq = False ):
nucleotide_match = ( cdr3_nucseq != '' )
if nucleotide_match:
assert not cdr3_protseq
cdr3_protseq = read_sanger_data.get_translation( cdr3_nucseq, '+1' )[0]
assert len(cdr3_nucseq) == 3 * len(cdr3_protseq )
ab = 'B'
assert v_gene[2] == 'B'
v_nucseq = get_v_cdr3_nucseq( organism, v_gene )
j_nucseq = get_j_cdr3_nucseq( organism, j_gene )
## what is the largest amount of these nucseqs we could preserve and still get cdr3_protseq
max_v_germline = 0
max_j_germline = 0
len_v_nucseq = len(v_nucseq)
len_j_nucseq = len(j_nucseq)
len_cdr3_nucseq = len(cdr3_nucseq)
len_cdr3_protseq = len(cdr3_protseq)
if nucleotide_match:
if allow_early_nucseq_mismatches:
mismatch_score = default_mismatch_score_for_cdr3_nucseq_probabilities
else:
mismatch_score = -100
max_v_germline = count_matches( v_nucseq, cdr3_nucseq, mismatch_score )
max_j_germline = count_matches( ''.join( reversed( list( j_nucseq ) )),
''.join( reversed( list( cdr3_nucseq ))),
mismatch_score )
if allow_early_nucseq_mismatches: ## obliterate the mismatches now
max_v, max_j = max_v_germline, max_j_germline
if max_v + max_j > len(cdr3_nucseq):
## some overlap!
extra = max_v + max_j - len(cdr3_nucseq )
#print 'TRIM extra',extra
fake_v_trim = extra/2 ## now dterministic
fake_j_trim = extra - fake_v_trim
max_v -= fake_v_trim
max_j -= fake_j_trim
old_cdr3_nucseq = cdr3_nucseq[:]
cdr3_nucseq = v_nucseq[:max_v] + \
cdr3_nucseq[ max_v : len_cdr3_nucseq-max_j ] + \
j_nucseq[len_j_nucseq-max_j:]
if old_cdr3_nucseq != cdr3_nucseq:
Log('early_cdr3a_nucseq_mismatch: before {} after {}'.format( old_cdr3_nucseq, cdr3_nucseq ) )
assert len(cdr3_nucseq) == len(old_cdr3_nucseq)
else:
## V
for i in range( len(v_nucseq)):
i_aa = i/3 ## which aa do we code for?
len_codon = (i%3) + 1
if i_aa >= len(cdr3_protseq): break
start = 3*i_aa
codon = v_nucseq[ start:start+len_codon]
target_aa = cdr3_protseq[ i_aa ]
matched = False
for c in reverse_genetic_code[target_aa]:
if c.startswith(codon):
matched = True
if verbose:
print 'V',codon, target_aa, matched
if matched:
max_v_germline = i+1
else:
break
## J
for i in range( len_j_nucseq):
i_aa = i/3 ## which aa do we code for?
len_codon = (i%3) + 1
if i_aa >= len(cdr3_protseq): break
end = len(j_nucseq)-3*i_aa
codon = j_nucseq[max(0,end-len_codon):end]
target_aa = cdr3_protseq[ len_cdr3_protseq-1-i_aa ]
matched = False
for c in reverse_genetic_code[target_aa]:
if c.endswith(codon):
matched = True
if verbose:
print 'J',codon, target_aa, matched
if matched:
max_j_germline = i+1
else:
break
if verbose:
print 'max_v_germline:',max_v_germline, len(v_nucseq)
## how about J?
min_insert = 3*len_cdr3_protseq - max_v_germline - max_j_germline
if verbose:
print 'max_j_germline:',max_j_germline, len_j_nucseq,cdr3_protseq,\
read_sanger_data.all_fasta[organism][ab]['J'][read_sanger_data.prot][j_gene]
print 'min_insert:',min_insert,max_v_germline,max_j_germline
trbj_index = int( j_gene[4] ) ## to decide which d genes to allow
assert trbj_index in [1,2]
total_prob = 0.0
min_extra_trim = max(0,-1*min_insert)
dids = tcr_rearrangement.all_trbd_nucseq[organism].keys()
for extra_trim in range(min_extra_trim,100):
old_total_prob = total_prob
total_prob_this_trim = 0.0
for extra_v_trim in range(0,extra_trim+1):
extra_j_trim = extra_trim - extra_v_trim
v_trim = len_v_nucseq - max_v_germline + extra_v_trim
j_trim = len_j_nucseq - max_j_germline + extra_j_trim
if v_trim > len_v_nucseq or j_trim > len_j_nucseq: continue
n_insert = min_insert + extra_v_trim + extra_j_trim
assert n_insert>=0 ## b/c of min_extra_trim
total_prob_this_insert = 0.0
## now we are looking to fit part of the D gene into this middle region and still code for the right aas
for did in dids:
if trbj_index == 1:
if did == 1:
did_prob = 1.0
else:
continue
else:
did_prob = 1.0/float(len(dids))
d_nucseq = tcr_rearrangement.all_trbd_nucseq[organism][did]
len_d_nucseq = len( d_nucseq )
for d0_trim in range(len_d_nucseq+1):
for d1_trim in range(len_d_nucseq+1):
len_d_insert = len_d_nucseq - d0_trim - d1_trim
if len_d_insert < 0 or len_d_insert > n_insert: continue
#if len_d_insert == 0 and d1_trim: continue ## only hit this one once!
d_insert = d_nucseq[ d0_trim: len_d_nucseq-d1_trim]
num_n = n_insert - len_d_insert
for num_n_before_d in range(num_n+1):
num_n_after_d = num_n - num_n_before_d
assert num_n_after_d>=0
n_nucseq = ( v_nucseq[:len_v_nucseq-v_trim] +
'n'*num_n_before_d + d_insert + 'n'*num_n_after_d +
j_nucseq[j_trim:] )
assert len(n_nucseq) == 3*len_cdr3_protseq
trim_prob = tcr_rearrangement.get_beta_trim_probs( organism, did,
v_trim, d0_trim, d1_trim, j_trim,
num_n_before_d, num_n_after_d )
if not trim_prob: continue
if nucleotide_match:
assert len(n_nucseq) == len_cdr3_nucseq
matched = True
#print n_nucseq, cdr3_nucseq
for a,b in zip( n_nucseq, cdr3_nucseq ):
if a!=b and a!= 'n':
matched=False
if matched:
coding_prob = 0.25 ** num_n
else:
coding_prob = 0.0
else:
coding_prob = get_coding_probability( n_nucseq, cdr3_protseq )
prob = did_prob * coding_prob * trim_prob
total_prob_this_insert += prob ## just for status output
total_prob_this_trim += prob
total_prob += prob
if verbose and coding_prob:
print 'coding_prob:',cdr3_protseq,"trims:",v_trim,d0_trim,d1_trim,j_trim,\
"inserts:",num_n_before_d,num_n_after_d,\
"d_insert:",d_insert,\
"total_prob:",total_prob,"prob:",prob,"coding_prob:",coding_prob,\
"trim_prob:",trim_prob,n_nucseq
if verbose:
print 'n_insert:',n_insert,extra_v_trim,extra_j_trim,'total_prob:',total_prob,\
'total_prob_this_insert:',total_prob_this_insert
if extra_trim>2 and total_prob_this_trim < error_threshold * old_total_prob:
break
if return_final_cdr3_nucseq:
return total_prob, cdr3_nucseq
else:
return total_prob
def alpha_cdr3_protseq_probability( organism, v_gene, j_gene, cdr3_protseq,
cdr3_nucseq = '', error_threshold = 0.05, verbose=False,
allow_early_nucseq_mismatches = True,
return_final_cdr3_nucseq = False ):
#assert organism == 'mouse' ## need new stats for human
nucleotide_match = ( cdr3_nucseq != '' )
if nucleotide_match:
assert not cdr3_protseq
cdr3_protseq = read_sanger_data.get_translation( cdr3_nucseq, '+1' )[0]
assert len(cdr3_nucseq) == 3 * len(cdr3_protseq )
ab = 'A'
assert v_gene[2] == 'A'
v_nucseq = get_v_cdr3_nucseq( organism, v_gene )
j_nucseq = get_j_cdr3_nucseq( organism, j_gene )
## what is the largest amount of these nucseqs we could preserve and still get cdr3_protseq
max_v_germline = 0
len_v_nucseq = len(v_nucseq)
max_j_germline = 0
len_j_nucseq = len(j_nucseq)
len_cdr3_protseq = len(cdr3_protseq)
len_cdr3_nucseq = len(cdr3_nucseq)
if nucleotide_match:
if allow_early_nucseq_mismatches:
mismatch_score = default_mismatch_score_for_cdr3_nucseq_probabilities
else:
mismatch_score = -100
max_v_germline = count_matches( v_nucseq, cdr3_nucseq, mismatch_score )
max_j_germline = count_matches( ''.join( reversed( list( j_nucseq ) )),
''.join( reversed( list( cdr3_nucseq ))),
mismatch_score )
if allow_early_nucseq_mismatches: ## obliterate the mismatches now
max_v, max_j = max_v_germline, max_j_germline
if max_v + max_j > len(cdr3_nucseq):
## some overlap!
extra = max_v + max_j - len(cdr3_nucseq )
#print 'TRIM extra',extra
fake_v_trim = extra/2 ## now dterministic
fake_j_trim = extra - fake_v_trim
max_v -= fake_v_trim
max_j -= fake_j_trim
old_cdr3_nucseq = cdr3_nucseq[:]
cdr3_nucseq = v_nucseq[:max_v] + \
cdr3_nucseq[ max_v : len_cdr3_nucseq-max_j ] + \
j_nucseq[len_j_nucseq-max_j:]
if old_cdr3_nucseq != cdr3_nucseq:
Log('early_cdr3a_nucseq_mismatch: {} {} before {} after {}'.format( v_gene, j_gene,
old_cdr3_nucseq, cdr3_nucseq ) )
assert len(cdr3_nucseq) == len(old_cdr3_nucseq)
else:
for i in range( len(v_nucseq)):
i_aa = i/3 ## which aa do we code for?
len_codon = (i%3) + 1
if i_aa >= len(cdr3_protseq): break
start = 3*i_aa
codon = v_nucseq[ start:start+len_codon]
target_aa = cdr3_protseq[ i_aa ]
matched = False
for c in reverse_genetic_code[target_aa]:
if c.startswith(codon):
matched = True
if verbose:
print 'V',codon, target_aa, matched
if matched:
max_v_germline = i+1
else:
break
## how about J?
for i in range( len_j_nucseq):
i_aa = i/3 ## which aa do we code for?
len_codon = (i%3) + 1
if i_aa >= len(cdr3_protseq): break
end = len(j_nucseq)-3*i_aa
codon = j_nucseq[max(0,end-len_codon):end]
target_aa = cdr3_protseq[ len_cdr3_protseq-1-i_aa ]
matched = False
for c in reverse_genetic_code[target_aa]:
if c.endswith(codon):
matched = True
if verbose:
print 'J',codon, target_aa, matched
if matched:
max_j_germline = i+1
else:
break
min_insert = 3*len_cdr3_protseq - max_v_germline - max_j_germline
if verbose:
print 'max_v_germline:',max_v_germline, len_v_nucseq, v_nucseq, cdr3_nucseq
print 'max_j_germline:',max_j_germline, len_j_nucseq, j_nucseq, cdr3_nucseq, \
read_sanger_data.all_fasta[organism][ab]['J'][read_sanger_data.prot][j_gene]
print 'min_insert:',min_insert,max_v_germline,max_j_germline
total_prob = 0.0
min_extra_trim = max(0,-1*min_insert)
for extra_trim in range(min_extra_trim,100):
old_total_prob = total_prob
total_prob_this_trim = 0.0
for extra_v_trim in range(0,extra_trim+1):
extra_j_trim = extra_trim - extra_v_trim
v_trim = len_v_nucseq - max_v_germline + extra_v_trim
j_trim = len_j_nucseq - max_j_germline + extra_j_trim
if v_trim > len_v_nucseq or j_trim > len_j_nucseq: continue
n_insert = min_insert + extra_v_trim + extra_j_trim
n_nucseq = v_nucseq[:len_v_nucseq-v_trim] + 'n'*n_insert + j_nucseq[j_trim:]
assert len(n_nucseq) == 3*len_cdr3_protseq
if nucleotide_match:
coding_prob = 0.25 ** n_insert
else:
coding_prob = get_coding_probability( n_nucseq, cdr3_protseq )
trim_prob = tcr_rearrangement.get_alpha_trim_probs( organism, v_trim, j_trim, n_insert )
total_prob_this_trim += coding_prob * trim_prob
total_prob += coding_prob * trim_prob
if verbose:
print 'coding_prob:',cdr3_protseq,v_trim,j_trim,n_insert,total_prob,coding_prob,trim_prob,n_nucseq
if extra_trim>2 and total_prob_this_trim < error_threshold * old_total_prob:
break
if return_final_cdr3_nucseq:
return total_prob, cdr3_nucseq
else:
return total_prob