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# Purpose: convert results from three-way interaction analysis to edge format.
# Usage: python process_3way_interaction.py output20160911.txt > edges.txt.interaction.wiggelab.timecourse
# Create on 9 Aug 2019 by Hui Lan <lanhui@zjnu.edu.cn>
from geneid2name import make_gene_name_AGI_map_dict, get_gene_name
def get_2tf_1target_1score(s):
'''
s looks like 'AT1G73870_AT1G73870, AT5G10570_AT5G10570, AT2G05100_LHCB2.1 19.287 | 0.843 0.998 0.155 | -0.915 0.924 1.839 | 0.918 -0.419'
'''
lst = s.split()
tf1 = lst[0].split('_')[0]
tf2 = lst[1].split('_')[0]
target = lst[2].split('_')[0]
score = lst[3]
return (tf1, tf2, target, score)
## main
import sys
from datetime import datetime
f = open(sys.argv[1])
lines = f.readlines()
f.close()
agi2name_dict = make_gene_name_AGI_map_dict('../Data/information/AGI-to-gene-names_v2.txt')
result = ''
for line in lines:
line = line.strip()
tf1, tf2, target, interaction_score_str = get_2tf_1target_1score(line)
target_str = target + ' ' + get_gene_name(target, agi2name_dict)
tf1_str = tf1 + ' ' + get_gene_name(tf1, agi2name_dict)
tf2_str = tf2 + ' ' + get_gene_name(tf2, agi2name_dict)
score_str = '0.5'
cond_str = '.'
curr_date = datetime.now().strftime('%Y%m%d')
method_or_tissue = 'interact.with.%s' % (tf2 + '(' + get_gene_name(tf2, agi2name_dict) + ')')
s = '\t'.join([target_str, tf1_str, score_str, 'mix', '15', cond_str, '.', curr_date, interaction_score_str.replace('-',''), method_or_tissue])
result += s + '\n'
method_or_tissue = 'interact.with.%s' % (tf1 + '(' + get_gene_name(tf1, agi2name_dict) + ')')
s = '\t'.join([target_str, tf2_str, score_str, 'mix', '15', cond_str, '.', curr_date, interaction_score_str.replace('-',''), method_or_tissue])
result += s + '\n'
print(result)
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