Mercurial > repos > bimib > cobraxy

comparison COBRAxy/ras_generator.py @ 309:38c9a958ea78 draft

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author francesco_lapi
date Thu, 22 May 2025 16:03:37 +0000
parents 0025449eadba
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308:797d0e002934 309:38c9a958ea78
6 import pandas as pd 6 import pandas as pd
7 import pickle as pk 7 import pickle as pk
8 import utils.general_utils as utils 8 import utils.general_utils as utils
9 import utils.rule_parsing as ruleUtils 9 import utils.rule_parsing as ruleUtils
10 from typing import Union, Optional, List, Dict, Tuple, TypeVar 10 from typing import Union, Optional, List, Dict, Tuple, TypeVar
11 import os
11 12
12 ERRORS = [] 13 ERRORS = []
13 ########################## argparse ########################################## 14 ########################## argparse ##########################################
14 ARGS :argparse.Namespace 15 ARGS :argparse.Namespace
15 def process_args(args:List[str] = None) -> argparse.Namespace: 16 def process_args(args:List[str] = None) -> argparse.Namespace:
210 gene_custom (dict or None): Custom gene data dictionary if provided. 211 gene_custom (dict or None): Custom gene data dictionary if provided.
211 212
212 Returns: 213 Returns:
213 dict: A dictionary containing gene data with gene IDs as keys and corresponding values. 214 dict: A dictionary containing gene data with gene IDs as keys and corresponding values.
214 """ 215 """
215 args = process_args() 216
216 for i in range(len(gene)): 217 for i in range(len(gene)):
217 tmp = gene.iloc[i, 0] 218 tmp = gene.iloc[i, 0]
218 gene.iloc[i, 0] = tmp.strip().split('.')[0] 219 gene.iloc[i, 0] = tmp.strip().split('.')[0]
219 220
220 gene_dup = [item for item, count in 221 gene_dup = [item for item, count in
225 gene_in_rule = None 226 gene_in_rule = None
226 227
227 if gene_dup: 228 if gene_dup:
228 if gene_custom == None: 229 if gene_custom == None:
229 230
230 if str(args.rules_selector) == 'HMRcore': 231 if str(ARGS.rules_selector) == 'HMRcore':
231 gene_in_rule = pk.load(open(args.tool_dir + '/local/pickle files/HMRcore_genes.p', 'rb')) 232 gene_in_rule = pk.load(open(ARGS.tool_dir + '/local/pickle files/HMRcore_genes.p', 'rb'))
232 233
233 elif str(args.rules_selector) == 'Recon': 234 elif str(ARGS.rules_selector) == 'Recon':
234 gene_in_rule = pk.load(open(args.tool_dir + '/local/pickle files/Recon_genes.p', 'rb')) 235 gene_in_rule = pk.load(open(ARGS.tool_dir + '/local/pickle files/Recon_genes.p', 'rb'))
235 236
236 elif str(args.rules_selector) == 'ENGRO2': 237 elif str(ARGS.rules_selector) == 'ENGRO2':
237 gene_in_rule = pk.load(open(args.tool_dir + '/local/pickle files/ENGRO2_genes.p', 'rb')) 238 gene_in_rule = pk.load(open(ARGS.tool_dir + '/local/pickle files/ENGRO2_genes.p', 'rb'))
238 239
239 utils.logWarning(f"{args.tool_dir}'/local/pickle files/ENGRO2_genes.p'", ARGS.out_log) 240 utils.logWarning(f"{ARGS.tool_dir}'/local/pickle files/ENGRO2_genes.p'", ARGS.out_log)
240 241
241 gene_in_rule = gene_in_rule.get(type_gene) 242 gene_in_rule = gene_in_rule.get(type_gene)
242 243
243 else: 244 else:
244 gene_in_rule = gene_custom 245 gene_in_rule = gene_custom
660 None 661 None
661 """ 662 """
662 # get args from frontend (related xml) 663 # get args from frontend (related xml)
663 global ARGS 664 global ARGS
664 ARGS = process_args(args) 665 ARGS = process_args(args)
665 print(ARGS.rules_selector) 666
666 # read dataset 667 # read dataset
667 dataset = read_dataset(ARGS.input, "dataset") 668 dataset = read_dataset(ARGS.input, "dataset")
668 dataset.iloc[:, 0] = (dataset.iloc[:, 0]).astype(str) 669 dataset.iloc[:, 0] = (dataset.iloc[:, 0]).astype(str)
669 670
670 # remove versioning from gene names 671 # remove versioning from gene names
671 dataset.iloc[:, 0] = dataset.iloc[:, 0].str.split('.').str[0] 672 dataset.iloc[:, 0] = dataset.iloc[:, 0].str.split('.').str[0]
672 673
673 # handle custom models 674 # handle custom models
674 model :utils.Model = ARGS.rules_selector 675 model :utils.Model = ARGS.rules_selector
676
675 if model is utils.Model.Custom: 677 if model is utils.Model.Custom:
676 rules = load_custom_rules() 678 rules = load_custom_rules()
677 reactions = list(rules.keys()) 679 reactions = list(rules.keys())
678 680
679 save_as_tsv(ras_for_cell_lines(dataset, rules), reactions) 681 save_as_tsv(ras_for_cell_lines(dataset, rules), reactions)