def main():
logic_pre = LogicPrep.LogicsPrep()
logic = Logic.Logics()
for i in range(1, 30):
FILE_NAME_LIST.append(str(i))
description_dict = logic_pre.read_dat_file_for_description(
WORK_DIR + CDS_EACH_FNAME, FILE_NAME_LIST)
cds_dict, sm_gene_diff_trscrpt = logic_pre.read_gtf_file_by_line_to_dict(
WORK_DIR + CDS_FNAME, description_dict)
logic.get_guide_ref(cds_dict, WORK_DIR + SEQ_FNAME, INITIAL_SEQ)
def merge_off_target_total():
util = Util.Utils()
logic_prep = LogicPrep.LogicsPrep()
logic = Logic.Logics()
off_trgt_dict = util.read_txt_to_dict(INITIAL_MRGE_OFF_TRGT)
for i in range(1, 30):
FILE_NAME_LIST.append(str(i))
seq_cnt_group_by_crpt_id = {}
re_off_trgt_dict = {}
first_merge_dict = {}
result_dict = {}
for f_num in FILE_NAME_LIST:
print("starting with file [" + str(f_num) + "]")
df_obj = util.read_excel_2_dataframe(WORK_DIR + CAS_OFF_EXCEL, f_num)
first_merge_dict = logic_prep.merge_excel_n_off_trgt(
df_obj, off_trgt_dict)
for cas_scr_opt in CAS_SCORE_OPT:
for off_trg_opt_arr in FILTER_OUT_OPT:
result_dict = logic.filter_out_by_rule(cas_scr_opt,
off_trg_opt_arr,
MAX_SEQ_NUM,
first_merge_dict,
result_dict)
seq_cnt_group_by_crpt_id = util.make_excel_w_off_trgt(
WORK_DIR + CAS_OFF_EXCEL + "off_trgt_", "total", result_dict,
seq_cnt_group_by_crpt_id)
re_off_trgt_dict = logic.get_re_off_target_seq(MAX_SEQ_NUM,
seq_cnt_group_by_crpt_id,
first_merge_dict,
re_off_trgt_dict)
util.make_tab_txt_seq_cnt_group_by_crpt_id(
WORK_DIR + CAS_OFF_EXCEL + "seq_cnt_group_by_crpt_id_",
seq_cnt_group_by_crpt_id)
util.make_tab_txt_re_off_target_seq(
WORK_DIR + CAS_OFF_EXCEL + "re_off_target_seq_", re_off_trgt_dict)
def merge_off_target_indi(self, init_off_trgt, f_nm_list, wrk_dir,
excel_path, max_num, filt_out_opt):
util = Util.Utils()
logic_prep = LogicPrep.LogicsPrep()
off_trgt_opt = filt_out_opt[0]
cas_scr_opt = filt_out_opt[1]
off_trgt_dict = util.read_txt_to_dict(init_off_trgt)
seq_cnt_group_by_crpt_id = {}
re_off_trgt_dict = {}
for f_num in f_nm_list:
print("starting with file [" + str(f_num) + "]")
df_obj = util.read_excel_2_dataframe(wrk_dir + excel_path, f_num)
first_merge_dict = logic_prep.merge_excel_n_off_trgt(
df_obj, off_trgt_dict)
result_dict = {}
for cas_opt in cas_scr_opt:
for off_trg_opt_arr in off_trgt_opt:
result_dict = self.filter_out_by_rule(
cas_opt, off_trg_opt_arr, max_num, first_merge_dict,
result_dict)
seq_cnt_group_by_crpt_id = util.make_excel_w_off_trgt(
wrk_dir + excel_path + "off_trgt_", f_num, result_dict,
seq_cnt_group_by_crpt_id)
re_off_trgt_dict = self.get_re_off_target_seq(
max_num, seq_cnt_group_by_crpt_id, first_merge_dict,
re_off_trgt_dict)
print("done with file [" + str(f_num) + "]\n")
util.make_tab_txt_seq_cnt_group_by_crpt_id(
wrk_dir + excel_path + "seq_cnt_group_by_crpt_id_",
seq_cnt_group_by_crpt_id)
util.make_tab_txt_re_off_target_seq(
wrk_dir + excel_path + "re_off_target_seq_", re_off_trgt_dict)
def get_guide_ref(self, cds_dict, path, init):
util = Util.Utils()
logic_pre = LogicPrep.LogicsPrep()
# result_dict = {}
idx = 1
for key, vals in cds_dict.items():
result_dict = {}
tmp_p_dict, tmp_m_dict = logic_pre.read_seq_dict(path, key, init)
for val_dict in vals.values():
if 'CDS' in val_dict:
cds_seq_arr = val_dict['CDS']
total_cds_len = 0
for cds_tmp in cds_seq_arr:
cds_seq_tmp = cds_tmp.split(" ")
total_cds_len = total_cds_len + (
int(cds_seq_tmp[1]) - int(cds_seq_tmp[0]) + 1)
prent_cds_len = 0
for cds_seq in cds_seq_arr:
cds_seq_exon_num = cds_seq.split(" ")
prent_cds_len = prent_cds_len + (
int(cds_seq_exon_num[1]) -
int(cds_seq_exon_num[0]) + 1)
for i in range(
int(cds_seq_exon_num[0]) + 1,
int(cds_seq_exon_num[1]) + 1):
if i in tmp_p_dict:
result_dict[idx] = {}
result_dict[idx].update({
'Target gene name':
val_dict['Target gene name']
})
result_dict[idx].update({
'Ensembl transcript ID':
val_dict['Ensembl transcript ID']
})
result_dict[idx].update({
'Ensembl Gene ID':
val_dict['Ensembl Gene ID']
})
if 'Description' in val_dict:
result_dict[idx].update({
'Description':
val_dict['Description']
})
result_dict[idx].update(
{'Position of Base After cut': i})
result_dict[idx].update(
{'Target context sequence': tmp_p_dict[i]})
result_dict[idx].update({'Strand': '+'})
result_dict[idx].update(
{'Exon Number': cds_seq_exon_num[2]})
# the pos ratio out of total CDS depends on which strand gene occurs
if '+' == val_dict['Strand']:
this_len = prent_cds_len - (
int(cds_seq_exon_num[1]) - i + 1)
result_dict[idx].update(
{'Ratio': this_len / total_cds_len})
else:
this_len = prent_cds_len - (
i - int(cds_seq_exon_num[0]) + 1)
result_dict[idx].update(
{'Ratio': this_len / total_cds_len})
idx = idx + 1
if i in tmp_m_dict:
result_dict[idx] = {}
result_dict[idx].update({
'Target gene name':
val_dict['Target gene name']
})
result_dict[idx].update({
'Ensembl transcript ID':
val_dict['Ensembl transcript ID']
})
result_dict[idx].update({
'Ensembl Gene ID':
val_dict['Ensembl Gene ID']
})
if 'Description' in val_dict:
result_dict[idx].update({
'Description':
val_dict['Description']
})
result_dict[idx].update(
{'Position of Base After cut': i})
result_dict[idx].update({
'Target context sequence':
tmp_m_dict[i].split(" ")[0]
})
result_dict[idx].update({
'Target context anti sequence':
tmp_m_dict[i].split(" ")[1]
})
result_dict[idx].update({'Strand': '-'})
result_dict[idx].update(
{'Exon Number': cds_seq_exon_num[2]})
# the pos ratio out of total CDS depends on which strand gene occurs
if '+' == val_dict['Strand']:
this_len = prent_cds_len - (
int(cds_seq_exon_num[1]) - i + 1)
result_dict[idx].update(
{'Ratio': this_len / total_cds_len})
else:
this_len = prent_cds_len - (
i - int(cds_seq_exon_num[0]) + 1)
result_dict[idx].update(
{'Ratio': this_len / total_cds_len})
idx = idx + 1
print("DONE file_" + key)
util.make_excel(result_dict, init, key)