/
generate_heatmap.py
131 lines (78 loc) · 2.59 KB
/
generate_heatmap.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
import json_scripts
import numpy as np
import pandas as pd
def main():
merge_exp_sigs()
def merge_exp_sigs():
load_sigs_to_json()
merge_sigs_to_mat()
def merge_sigs_to_mat():
tmp_exp_sigs = json_scripts.load_to_dict('proc_data/exp-pert_sigs.json')
exp_sigs = {}
for inst_sig in tmp_exp_sigs:
if 'CD34' not in inst_sig:
exp_sigs[inst_sig] = tmp_exp_sigs[inst_sig]
all_sigs = sorted(exp_sigs.keys())
num_sigs = len(all_sigs)
print('num_sigs: ' + str(num_sigs))
# collect all genes across all experimental signatures
all_genes = []
for sig_name in exp_sigs:
inst_sig = exp_sigs[sig_name]
for inst_gene in inst_sig:
# fix sept problems
if '-SEP' in inst_gene:
inst_num = inst_gene.split('-')[0]
inst_gene = 'SEPT'+inst_num
if inst_gene != '-':
all_genes.append(inst_gene)
print(len(all_genes))
all_genes = sorted(list(set(all_genes)))
print(len(all_genes))
num_genes = len(all_genes)
print('there are ' + str(num_genes) + ' unique genes')
mat = np.zeros([num_genes, num_sigs])
# fill in the matrix
for sig_name in exp_sigs:
inst_sig = exp_sigs[sig_name]
col_index = all_sigs.index(sig_name)
for inst_gene in inst_sig :
# initialize value as false
inst_value = False
if inst_gene in all_genes:
inst_value = inst_sig[inst_gene]
if inst_value != False:
row_index = all_genes.index(inst_gene)
# fill in matrix
mat[row_index, col_index] = inst_value
# save as dataframe
df = pd.DataFrame(data=mat, columns = all_sigs, index = all_genes)
df.to_csv('proc_data/exp-pert_sigs.txt', sep='\t')
def load_sigs_to_json():
import glob
print('load')
# normal files
file_names = glob.glob('files_2-17-2017/hdf_day*.txt')
pert_files = glob.glob('files_2-17-2017/Pert*.txt')
file_names = file_names + pert_files
print('\n\n')
print(file_names)
print('\n\n')
# # full char dir files
# file_names = glob.glob('files_2-17-2017/big*.txt')
# store all signatures in a dictionary
exp_sigs = {}
for inst_filename in file_names:
inst_sig = inst_filename.split('.txt')[0].split('/')[1].split('_chdir')[0]
# initialize dictionary for signature
exp_sigs[inst_sig] = {}
f = open(inst_filename, 'r')
lines = f.readlines()
for inst_line in lines:
inst_line = inst_line.strip().split(',')
inst_gene = inst_line[0]
inst_value = inst_line[1]
exp_sigs[inst_sig][inst_gene] = inst_value
f.close()
json_scripts.save_to_json(exp_sigs, 'proc_data/exp-pert_sigs.json', indent='indent')
main()