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helper.py
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helper.py
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import numpy as np
import fileinput
import pickle
def filter_mutations(x):
assert isinstance(x, str)
return x[17:47]
def make_Sequence_Hash(file_name):
cdr1_start = 'GTGT'
cdr3_start = 'GTGA'
sequences = ["ACCCCAGTAGTCCATACCATAGTAAGAACC", "ACTTTTAGTGACTACTGGATGAACTGGGTC"]
sequence_hash = {sequences[0]: 0, sequences[1]: 1}
cdr = [3, 1]
count = len(sequences)
for line in fileinput.input([file_name]):
mutation = filter_mutations(line)
if mutation not in sequence_hash:
sequence_hash[mutation] = count
sequences.append(mutation)
start = line[0:4]
if start == cdr1_start:
cdr.append(1)
elif start == cdr3_start:
cdr.append(3)
count += 1
fileinput.close()
return sequence_hash, sequences, cdr
nt_complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'N': 'N', '-': '-'}
def comp_rev(x):
x=x[::-1]
x=[nt_complement[ii] for ii in x]
x=''.join(x)
return x
def check_nt2aa(codon):
if 'N' in codon:
return 'X'
elif '-' in codon:
return '-'
elif len(codon)!=3:
return ''
else:
return nt_aa_dict[codon]
def nt2aa(x):
x=x.upper()
out=[check_nt2aa(x[ind:ind+3]) for ind in range(0,len(x),3)]
return ''.join(out)
def aa2int(x):
out=[aa_int_dict[residue] for residue in x]
return np.array(out)
def nt2codon(x):
x=x.upper()
out=[nt_codon_dict[x[ind:ind+3]] for ind in range(0,len(x),3)]
out=np.array(out)
return out
aa_int_dict={'A':0,
'C':1,
'D':2,
'E':3,
'F':4,
'G':5,
'H':6,
'I':7,
'K':8,
'L':9,
'M':10,
'N':11,
'P':12,
'Q':13,
'R':14,
'S':15,
'T':16,
'V':17,
'W':18,
'Y':19,
'*':20}
aa_keys=aa_int_dict.keys()
int_aa_dict={}
for key in aa_keys:
curr_int=aa_int_dict[key]
int_aa_dict[curr_int]=key
nt_aa_dict={'ATT':'I',
'ATC':'I',
'ATA':'I',
'CTT':'L',
'CTC':'L',
'CTA':'L',
'CTG':'L',
'TTA':'L',
'TTG':'L',
'GTT':'V',
'GTC':'V',
'GTA':'V',
'GTG':'V',
'TTT':'F',
'TTC':'F',
'ATG':'M',
'TGT':'C',
'TGC':'C',
'GCT':'A',
'GCC':'A',
'GCA':'A',
'GCG':'A',
'GGT':'G',
'GGC':'G',
'GGA':'G',
'GGG':'G',
'CCT':'P',
'CCC':'P',
'CCA':'P',
'CCG':'P',
'ACT':'T',
'ACC':'T',
'ACA':'T',
'ACG':'T',
'TCT':'S',
'TCC':'S',
'TCA':'S',
'TCG':'S',
'AGT':'S',
'AGC':'S',
'TAT':'Y',
'TAC':'Y',
'TGG':'W',
'CAA':'Q',
'CAG':'Q',
'AAT':'N',
'AAC':'N',
'CAT':'H',
'CAC':'H',
'GAA':'E',
'GAG':'E',
'GAT':'D',
'GAC':'D',
'AAA':'K',
'AAG':'K',
'CGT':'R',
'CGC':'R',
'CGA':'R',
'CGG':'R',
'AGA':'R',
'AGG':'R',
'TAA':'*',
'TAG':'*',
'TGA':'*'}
nt_codon_dict={'ATT':0,
'ATC':1,
'ATA':2,
'CTT':3,
'CTC':4,
'CTA':5,
'CTG':6,
'TTA':7,
'TTG':8,
'GTT':9,
'GTC':10,
'GTA':11,
'GTG':12,
'TTT':13,
'TTC':14,
'ATG':15,
'TGT':16,
'TGC':17,
'GCT':18,
'GCC':19,
'GCA':20,
'GCG':21,
'GGT':22,
'GGC':23,
'GGA':24,
'GGG':25,
'CCT':26,
'CCC':27,
'CCA':28,
'CCG':29,
'ACT':30,
'ACC':31,
'ACA':32,
'ACG':33,
'TCT':34,
'TCC':35,
'TCA':36,
'TCG':37,
'AGT':38,
'AGC':39,
'TAT':40,
'TAC':41,
'TGG':42,
'CAA':43,
'CAG':44,
'AAT':45,
'AAC':46,
'CAT':47,
'CAC':48,
'GAA':49,
'GAG':50,
'GAT':51,
'GAC':52,
'AAA':53,
'AAG':54,
'CGT':55,
'CGC':56,
'CGA':57,
'CGG':58,
'AGA':59,
'AGG':60,
'TAA':61,
'TAG':62,
'TGA':63}
codon_keys=nt_codon_dict.keys()
int_ntcodon_dict={}
for key in codon_keys:
curr_int=nt_codon_dict[key]
int_ntcodon_dict[curr_int]=key
codon_int2aa= {0:'I',
1:'I',
2:'I',
3:'L',
4:'L',
5:'L',
6:'L',
7:'L',
8:'L',
9:'V',
10:'V',
11:'V',
12:'V',
13:'F',
14:'F',
15:'M',
16:'C',
17:'C',
18:'A',
19:'A',
20:'A',
21:'A',
22:'G',
23:'G',
24:'G',
25:'G',
26:'P',
27:'P',
28:'P',
29:'P',
30:'T',
31:'T',
32:'T',
33:'T',
34:'S',
35:'S',
36:'S',
37:'S',
38:'S',
39:'S',
40:'Y',
41:'Y',
42:'W',
43:'Q',
44:'Q',
45:'N',
46:'N',
47:'H',
48:'H',
49:'E',
50:'E',
51:'D',
52:'D',
53:'K',
54:'K',
55:'R',
56:'R',
57:'R',
58:'R',
59:'R',
60:'R',
61:'*',
62:'*',
63:'*'}
import matplotlib as mpl
cdict = {'red': ((0.0, 1, 1),
(0.1, 1, 1),
(0.2, 0.65, 0.65),
(0.5, 1.0, 1.0),
(1.0, 1, 1)),
'green': ((0.0, 1, 1),
(0.1, 1, 1),
(0.2, 0.35, 0.35),
(0.5, 0.35, 0.35),
(1.0, 1, 1)),
'blue': ((0.0, 1, 1),
(0.1, 1, 1),
(0.2, 0.05, 0.05),
(1.0, 0.05, 0.05))}
brown_yellow = mpl.colors.LinearSegmentedColormap('my_colormap',cdict,256)
cdict = {'red': ((0.0, 0.65, 0.65),
(0.5, 1.0, 1.0),
(1.0, 1, 1)),
'green': ((0.0, 0.35, 0.35),
(0.5, 0.35, 0.35),
(1.0, 1, 1)),
'blue': ((0.0, 0.05, 0.05),
(1.0, 0.05, 0.05))}
brown_yellow2 = mpl.colors.LinearSegmentedColormap('my_colormap',cdict,256)
cdict = {'red': ((0.0, 1, 1),
(0.19, 1, 1),
(0.2, 0.65, 0.65),
(0.5, 1.0, 1.0),
(1.0, 1, 1)),
'green': ((0.0, 1, 1),
(0.19, 1, 1),
(0.2, 0.35, 0.35),
(0.5, 0.35, 0.35),
(1.0, 1, 1)),
'blue': ((0.0, 1, 1),
(0.19, 1, 1),
(0.2, 0.05, 0.05),
(1.0, 0.05, 0.05))}
brown_yellow3 = mpl.colors.LinearSegmentedColormap('my_colormap',cdict,256)
cdict = {'red': ((0.0, 1, 0.75),
(0.25, 1, 0.875),
(0.47, 1, 1),
(0.53, 1, 1),
(0.75, 0.5, 0.5),
(1.0, 0.25, 0.25)),
'green': ((0.0, 0.5, 0.5),
(0.25, 0.75, 0.75),
(0.47, 1, 1),
(0.53, 1, 1),
(0.75, 0.875, 0.875),
(1.0, 0.75, 0.75)),
'blue': ((0.0, 0, 0),
(0.25, 0, 0),
(0.47, 1, 1),
(0.53, 1, 1),
(0.75, 0.2, 0.1),
(1.0, 0.0, 0.0))}
red_green = mpl.colors.LinearSegmentedColormap('my_colormap',cdict,256)
aa_colors = {
'K': [0, 0, 1],
'R': [0, 0, 1.0000],
'H': [0, 0, 1.0000],
'C': [0.2500, 1.0000, 0.7500],
'F': [1.0000, 0.8125, 0],
'G': [1.0000, 0.8125, 0],
'A': [1.0000, 0.8125, 0],
'I': [1.0000, 0.8125, 0],
'L': [1.0000, 0.8125, 0],
'M': [1.0000, 0.8125, 0],
'N': [0.2500, 1.0000, 0.7500],
'Q': [0.2500, 1.0000, 0.7500],
'P': [1.0000, 0.8125, 0],
'S': [0.2500, 1.0000, 0.7500],
'T': [0.2500, 1.0000, 0.7500],
'V': [1.0000, 0.8125, 0],
'W': [1.0000, 0.8125, 0],
'Y': [0.2500, 1.0000, 0.7500],
'D': [1, 0, 0],
'E': [1, 0, 0],
'*': [0, 0, 0]}
aa_colors2 = {
'K': [0, 0, 0.8000],
'R': [0, 0, 0.8000],
'H': [0, 0, 0.8000],
'C': [0.9, 0.5, 0.2],
'F': [1.0000, 0.8125, 0],
'G': [1.0000, 0.8125, 0],
'A': [1.0000, 0.8125, 0],
'I': [1.0000, 0.8125, 0],
'L': [1.0000, 0.8125, 0],
'M': [1.0000, 0.8125, 0],
'N': [0.0000, 0.8000, 0.0000],
'Q': [0.0000, 0.8000, 0.0000],
'P': [0.9, 0.5, 0.2],
'S': [0.0000, 0.8000, 0.0000],
'T': [0.0000, 0.8000, 0.0000],
'V': [1.0000, 0.8125, 0],
'W': [1.0000, 0.8125, 0],
'Y': [1.0000, 0.8125, 0],
'D': [0.8, 0, 0],
'E': [0.8, 0, 0],
'*': [0, 0, 0]}
mut_colors = {
0: [0, 0, 0.8],
1: [0, 0, 0],
2: [0, 1, 0],
3: [1, 0, 0],
4: [0.5, 0, 0.5],
5: [0.5, 0.5, 0],
6: [0, 0.5, 0.5]}
# Only used in Fig. 4.
# ['P','E', 'V','N','L']
#syn_colors = { 'E':[0,1,0], # Glutamic acid, Green
# 'P':[1,1,0], # Proline, Yellow
# 'L':[1,0,1], # Leucine, Magenta
# 'N':[1,.5,0],# Asparagine, Orange
# 'V':[0,1,1]} # Cysteine, Cyan
syn_colors = {'R':[0.5,0.5,1],
'H':[0,0,1],
'Y':[0,0.8,0],
'S':[0,0.0,0.8],
'D':[0.8,0,0],
'E':[1,0.5,0.5],
'G':[0,0.5,0.2],
'P':[1,0.8,0.2],
'A':[0.2,0.2,0.2],
'C':[0.0,1,0.3],
'F':[0,0.5,0],
'I':[0.4,0,0.4],
'L':[0.7,0,0.7],
'M':[0.7,0.7,0.7],
'N':[1,0,1],
'Q':[1,0.4,1],
'T':[0.3,1,0],
'V':[0,0.8,0.8],
'W':[0.2,0.2,0.2],
'K':[0,0,0.7]}