# HG changeset patch # User bimib # Date 1730916142 0 # Node ID 9cb6eaa3c2b8fa0d3573a853124cde7c6a78a2d9 # Parent 60e96b950829e89a2801899365a53d942d87a5c5 Uploaded diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/README.md diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/custom_data_generator.py --- a/marea_2/custom_data_generator.py Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/custom_data_generator.py Wed Nov 06 18:02:22 2024 +0000 @@ -6,11 +6,11 @@ import pandas as pd import utils.general_utils as utils import utils.rule_parsing as rulesUtils -from typing import Optional, Tuple, Union, Dict +from typing import Optional, Tuple, Union, List, Dict import utils.reaction_parsing as reactionUtils ARGS : argparse.Namespace -def process_args() -> argparse.Namespace: +def process_args(args:List[str] = None) -> argparse.Namespace: """ Interfaces the script of a module with its frontend, making the user's choices for various parameters available as values in code. @@ -35,9 +35,8 @@ parser.add_argument("-id", "--input", type = str, required = True, help = "Input model") parser.add_argument("-mn", "--name", type = str, required = True, help = "Input model name") # ^ I need this because galaxy converts my files into .dat but I need to know what extension they were in - - argsNamespace = parser.parse_args() - argsNamespace.out_dir = "result" + parser.add_argument('-idop', '--output_path', type = str, default='result', help = 'output path for maps') + argsNamespace = parser.parse_args(args) # ^ can't get this one to work from xml, there doesn't seem to be a way to get the directory attribute from the collection return argsNamespace @@ -184,7 +183,7 @@ writer.writerow({ fieldNames[0] : key, fieldNames[1] : value }) ###############################- ENTRY POINT -################################ -def main() -> None: +def main(args:List[str] = None) -> None: """ Initializes everything and sets the program in motion based on the fronted input arguments. @@ -193,10 +192,10 @@ """ # get args from frontend (related xml) global ARGS - ARGS = process_args() + ARGS = process_args(args) # this is the worst thing I've seen so far, congrats to the former MaREA devs for suggesting this! - if os.path.isdir(ARGS.out_dir) == False: os.makedirs(ARGS.out_dir) + if os.path.isdir(ARGS.output_path) == False: os.makedirs(ARGS.output_path) # load custom model model = load_custom_model( diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/ENGRO2_rules.csv diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/desktop.ini diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/medium/medium.csv --- a/marea_2/local/medium/medium.csv Thu Sep 19 10:00:47 2024 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,35 +0,0 @@ -engro2_name,RPMI 1640,DMEM,EMEM,DMEM:F12 = 1:1,McCoy's 5A,IMDM,MEM,GMEM,Leibovitz's L-15,F12,F10,AMEM,Waymouth MB 7521 medium,F12K,William's E Medium,Medium 199,MCDB 105,NEAA,RPMI:F12 = 1:1,RPMI:MEM = 1:1,RPMI:EMEM = 1:1,EMEM:F12 = 1:1,DMEM:RPMI = 2:1,DMEM:IMDM = 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- - - - - - diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/ENGRO2_genes.p diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/ENGRO2_genes.pickle diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/ENGRO2_rules.p diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/HMRcore_genes.p diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/HMRcore_genes.pickle diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/HMRcore_rules.p diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/RECON_genes.pickle diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/Recon_genes.p diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/Recon_rules.p diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/black_list.pickle diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/reactions.pickle diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/synonyms.pickle diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/pickle files/synonyms_dict_recon_keys_filtered.pkl Binary file marea_2/local/pickle files/synonyms_dict_recon_keys_filtered.pkl has changed diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/readme.txt diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/svg metabolic maps/ENGRO2_map.svg --- a/marea_2/local/svg metabolic maps/ENGRO2_map.svg Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/local/svg metabolic maps/ENGRO2_map.svg Wed Nov 06 18:02:22 2024 +0000 @@ -1,20105 +1,3104 @@ - - - - - - - - - AC - ATP - CoA - - - - - - Legend: - - = Up regulated - = Down regulated - - - - - - - - - = Not classified - = Not significant - = Fold change under threshold - Thickness is proportional to fold change - - - - - - CySS - CySS - Ala - Ala - - - - Ser - Ser - CySS - CySS - - - - - - CySS - CySS - Leu - Leu - - - - CySS - CySS - Glu - - Glu - - - Chol - - - - - - Palm - - - - - - - Ala - - Asp - - - Arg - - - - - Glu - Ser - - Gly - - - Asn - - Tyr - - Cys - - Pro - Gln - - - His - - - Leu - - - Ile - - - Lys - Met - - - Phe - - - Thr - - - Trp - - - - Val - - - - - - - - - - - - - - - - - - - - - - - - - BH4 - - - - BH2 - - - - - - - - - O - ₂ - - - - - - - - - - - - - - Pi - - - - HO - ₂ - - - - - - H - - - - - CO - ₂ - - - - - - - - - - hcarn - - - - - 4abut - - - - - anth - - - - - - Orn - Arg - - HO - ₂ - - - NH - ₃ - - Ci - Gly - - SAH - - - - Creatine - SAM - GA - - - - - - - CreatineP - ATP - ADP - - - Creatinine - - H - ⁺ - - Pi - - - - - - - - - - - - - - DHF - - - - - NADP - ⁺ - - - H - ⁺ - - NADPH - - - Folate - - - - - NADP - ⁺ - - - H - ⁺ - - NADPH - - 10formylTHF - - - H - ⁺ - - - HO - ₂ - - - - - - - - HO - ₂ - - - NADP - ⁺ - - NADPH - - CO - ₂ - - - H - ⁺ - - Formate - THF - Pi - ADP - - - - ATP - - - - - - 5,10mTHF - 5,10meTHF - - - - - NADH - - NAD - ⁺ - - - - - - - NADPH - - NADP - ⁺ - - - - - - 2 H - - NH - ₃ - - 5forthf - - - - NADPH - - 2 - H - - NADP - - 5mTHF - - - - - - Amino acids synthesis / degradation - - - - - - Pentose Phosphate pathway - - - - - - Nucleotide synthesis - - - - - - Fatty acids / Cholesterol synthesis - - - - - - Urea cycle - - - - - - Ammonia detox - - - - - - Biomass - - - - - - Fatty acids β-oxidation - - - - - - Glutathione synthesis - - - - - - Glycolysis / Gluconeogenesis - - - - Ala - AKG - Glu - - - - - - GSSG - - GSH - - - H - ⁺ - - NADH - - NAD - ⁺ - - - HO - ₂₂ - - GSH - - - 2 HO - ₂ - - GSH - - - - - NADP - ⁺ - - GSH - - - H - ⁺ - - NADPH - - - - - - - - - - GC - Cys - - ATP - - - Gly - Pi - ADP - - - ATP - - - Glu - Pi - ADP - - - - - Mitochondrial space - - - - Glc - Glc - G6P - F6P - F1,6BP - GA3P - ATP - ADP - - NAD - ⁺ - - NADH - - - - - - - - ATP - ADP - - - - - - Pi - - - - - - HO - ₂ - - Pi - - HO - ₂ - - Pi - - - - - - - - 1,3BPGA - 3PG - 2PG - ADP - ATP - - - - - - 2,3BPG - - HO - ₂ - - Pi - - - - - - - - - PEP - - - Pyr - - ADP - ATP - - - Lact - - - H - ⁺ - - NADH - - NAD - ⁺ - - - - - - - - - - - - HO - ₂ - - - - - Putr - - - - ametam - 5mta - - spermidine - - - - ametam - 5mta - - spermine - - - ⁺ - H - - - ₂ - CO - - - - SAM - - 5mdr1p - - - 5mdru1p - - - - - ₂ - HO - - - dkmpp - met - - Gln - - 2 H - ⁺ - - Glu - - - - - - HO - ₂ - - ATP - Pi - PPi - - - - SAM - - THF - 5mTHF - - - - SAH - - - HO - ₂ - - Adenosine - - - - - - Pi - adenine - - - - PRPP - PPi - AMP - - - - - ATP - - H - ⁺ - - ADP - AMP - - - - - Hcys - - - 5mTHF - THF - - - - - - - - - - ₂ - HO - - - ₂ - O - - Pi - - ⁺ - 2 H - - formate - - 2kmb - - - - Glu - AKG - - - - - - ₂ - CO - - - - hcarn - ATP - AMP - PPi - His - - 2 H - ⁺ - - - - - - - - ₂ - HO - - His - - - - 4abutn - - - ₂ - HO - - - NAD - ⁺ - - - - - 4abut - - ₂ - CO - - - H - ⁺ - - NADH - - - Glu - - - - - ₂ - HO - - - ₂ - O - - - ₂₂ - HO - - - ₃ - NH - - - - - Putr - - - - - - - - spermine - - - - - spermidine - - - - - - 2obut - - - - 6Pgl - - NADP - ⁺ - - NADPH - - H - ⁺ - - 6PDG - - NADP - ⁺ - - NADPH - - CO - ₂ - - - H - ⁺ - - Ru5P - - - HO - ₂ - - - - - - - - AMP - ATP - - - R5P - - - - - Xil5P - - - - - Sed7P - GA3P - - - - F6P - Sed1,7BP - Ery4P - DHAP - ATP - ADP - - - - - - - Ery4P - - - - GA3P - F6P - Xil5P - - - - ADP - ATP - dTTP - - - - - - - - PRPP - Gly - 2 10fTHF - 2 THF - PPi - 4 ADP - Fum - 2 Gln - 2 Glu - 4 ATP - Asp - - HO - ₂ - - - CO - ₂ - - Asp - 2 ATP - - QH - ₂ - - 2 ADP - Gln - Glu - - HCO - ₃ - ⁻ - - Q - - H - ⁺ - - PPi - - CO - ₂ - - UDP - ATP - ADP - dUDP - - HO - ₂ - - - - dUMP - ADP - ATP - dTMP - 5,10meTHF - DHF - UTP - CTP - ADP - Pi - ATP - - NH - ₃ - - CDP - - HO - ₂ - - dCDP - ATP - ADP - - - - - - - - - UMP - GMP - GDP - dGDP - - 2 - HO - - AMP - ADP - ADP - ATP - - HO - ₂ - - dADP - - - - - - - - - ADP - ATP - dGTP - ADP - ATP - - - - - - - dATP - dCTP - dTDP - 4 Pi - - - IMP - 2 Pi - - - - - - - - ADP - ATP - - - - - - - ADP - ATP - - - - - - ADP - ATP - - - - - - - - - - GTP - Asp - GDP - Pi - Fum - - NAD - ⁺ - - - HO - ₂ - - ATP - - NH - ₃ - - NADH - - H - ⁺ - - AMP - PPi - - - NADP - ⁺ - - - NH - ₃ - - - H - ⁺ - - NADPH - - - - - - ADP - ATP - - - - - - - - - - - - - - - ADP - ATP - GTP - - - - - - - - - - - - - - - - - - - - ATP - - HCO - ⁻ - ₃ - - - H - ⁺ - - ADP - Pi - - - - CoA - AcACP - ACP - - - - - - CO - ₂ - - - ACP - - - - MalCoA - - CoA - MalACP - ACP - - - - AcCoA - - HO - ₂ - - CoA - AcAcCoA - - - - - PalmCoA - CoA - AMP - PPi - ATP - - - Palm - - - AcAcACP - 14 NADPH - - 14 NADP - ⁺ - - - 6 HO - ₂ - - - 6 CO - ₂ - - 6 MalACP - 7 ACP - - - 14 H - ⁺ - - - - - HMGCoA - 3 ATP - CoA - 2 NADPH - - 2 NADP - ⁺ - - 3 ADP - - CO - ₂ - - Pi - - - - - 2 PPi - fPP - 2 ippPP - ippPP - - - - - 13 NADPH - - 2 - 10 O - - - 13 NADP - ⁺ - - 2 PPi - formate - - 2 CO - ₂ - - Chol - fPP - - 15 HO - ₂ - - - - - 16 H - ⁺ - - - AcCoA - - HMGCoA - - - - - - AcCoA - CoA - - - - - - - - 3 - NH - - - - - - Ci - - - 3 - NH - - - H - ⁺ - - - ⁻ - ₃ - HCO - - 2 ADP - Pi - - - 2 ATP - - Orn - - H - ⁺ - - - Orn - - H - ⁺ - - - Ci - - CP - Pi - Orn - - - - - - - - - Pi - - H - ⁺ - - Pi - - - ATP - ADP - ATP - ADP - - - GTP - GDP - GTP - GDP - - - - - HO - ₂ - - - HO - ₂ - - - - O - ₂ - - - O - ₂ - - - - - NADH - - NAD - ⁺ - - - 0.95 QH - ₂ - - - 4.75 H - ⁺ - - 0.95 Q - - 3.8 H - ⁺ - - - FADH - ₂ - - FAD - - QH - ₂ - - Q - - 2 Cytc-ox - 2 Cytc-red - Q - - 2 H - ⁺ - - - QH - ₂ - - - - 4 H - ⁺ - - 4 Cytc-red - 4 Cytc-ox - - 2 HO - ₂ - - - 8 H - ⁺ - - - O - ₂ - - - - GSH - GSH - - - - Pi - Pi - - - - Gly - Gly - - Mal - AKG - AKG - - - - ADP - Pi - ATP - - HO - ₂ - - - 4 H - ⁺ - - 10-formylTHF - 5,10mTHF - - HO - ₂ - - 5,10meTHF - - - - NADPH - - NADP - ⁺ - - - H - ⁺ - - THF - - HO - ₂ - - - CO - ₂ - - - CO - ₂ - - - - - - NADH - NADPH - - NADP - ⁺ - - - NAD - ⁺ - - - - H - ⁺ - - - - H - ⁺ - - - - - HO - ₂₂ - - - 2 HO - ₂ - - 2 GSH - - O - ₂ - ⁻ - - - O - ₂ - ⁻ - - - 2 H - ⁺ - - - O - ₂ - - - - GSSG - - - - - NADH - - H - ⁺ - - - NAD - ⁺ - - NADPH - - H - ⁺ - - - NADP - ⁺ - - - - - - - - - CO - ₂ - - - HCO - ₃ - ⁻ - - - - H - ⁺ - - - HO - ₂ - - - - ADP - - - - Ser - Ser - - - - 0.05 O - ₂ - - - - 0.05 O - ₂ - ⁻ - - - - DHAP - DHAP - FAD - - - FADH - ₂ - - - Gly3P - Gly3P - - - - - AcCoA - Pyr - - - NAD - ⁺ - - - NADP - ⁺ - - NADH - - CO - ₂ - - - H - ⁺ - - - - - - Pi - ADP - - H - ⁺ - - ATP - - HCO - ₃ - ⁻ - - - NAD - ⁺ - - CoA - - 2 - CO - - - H - ⁺ - - NADH - - - - - - - - - NADPH - - H - ⁺ - - - CO - ₂ - - - - - - Pi - - - - - - ATP - - - - Formate - - - Formate - - Formate - - - - - - - - - - H - ⁺ - - - H - ⁺ - - - H - ⁺ - - Mal - - H - ⁺ - - - OAA - Cit - Isocit - AKG - - NADP - ⁺ - - SuCoA - Succ - Fum - Mal - - FAD - - FADH - ₂ - - - NAD - ⁺ - - - - HO - ₂ - - CoA - - - - - HO - ₂ - - - - - - - - NADH - - H - ⁺ - - - - - GDP - Pi - CoA - GTP - - - - - CoA - - NAD - ⁺ - - - - NADH - - CO - ₂ - - - H - ⁺ - - - - NADPH - ⁺ - - - CO - ₂ - - - H - ⁺ - - - - - - NAD - ⁺ - - - NADH - ⁺ - - - H - ⁺ - - - CO - ₂ - - - - - - - - - - - - - - - - - NADH - - H - ⁺ - - - NH - ₃ - - - NAD - ⁺ - - - HO - ₂ - - NADPH - - H - ⁺ - - - NH - ₃ - - - NADP - ⁺ - - - HO - ₂ - - - - - - - - - - NADP - ⁺ - - NADPH - - H - ⁺ - - DHF - - - - - NADP - ⁺ - - NADPH - - H - ⁺ - - Folate - - - - - 4 H - ⁺ - - - 4 H - ⁺ - - - NADH - - H - ⁺ - - - HO - ₂ - - - NAD - ⁺ - - - - - Gln - Glu - - - Gln - - - - NH - ₃ - - Glu - - HO - ₂ - - - - - H - ⁺ - - - H - ⁺ - - - H - ⁺ - - - H - ⁺ - - - Folate - - - - + - H - - Mal - - Fum - - - - Pi - Pi - Fum - - - GluSA - - - - GluSA - - - - - - - - - - - - - - - - - Val, 3mob, propCoA - - - Leu - Leu - - - - - - Val - Val - - - - - - - - - H - ⁺ - - - H - ⁺ - - Lys - Lys - - - 3mob - 3mob - - H - ⁺ - - - H - ⁺ - - - - - - 4mop - 4mop - - H - ⁺ - - - H - ⁺ - - - - - - 2oxoadp - 2oxoadp - - AKG - AKG - - - propCoA - propCoA - - - - - - 5,10meTHF - 5,10meTHF - - - - - - AKG - Glu - - - - - - - Asp - Glu - - H - ⁺ - - - H - ⁺ - - Glu - - - - - AcAcCoA - - - CoA - 2 AcCoA - - - - NADH - - NAD - ⁺ - - - H - ⁺ - - - - - - - - - - - - - - - - - - - - - - - - HMGCoA - Leu, 4mop - Lys, 2oxoadp - - AcCoA - - HO - ₂ - - CoA - - H - ⁺ - - - - HO - ₂ - - - - - - - - - - - - - - Ci - Orn - ArgSuc - Arg - Fum - - - HO - ₂ - - - Urea - - - - - - - - - 3 - NH - - - - - PalmCarn - PalmCarn - - - - Carn - Carn - PalmCoA - - - - Carn - CoA - 8 AcCoA - 7 FAD - - 7 NAD - ⁺ - - 7 CoA - - 7 HO - ₂ - - - - 7 FADH - ₂ - - 7 NADH - - 7 H - ⁺ - - - - - - H - ⁺ - - - CO - ₂ - - - HCO - ₃ - ⁻ - - - - HO - ₂ - - - ADP - Pi - - HO - ₂ - - ATP - - - - H - ⁺ - - PPi - Pi - Pi - - HO - ₂ - - - - - - 0.01 dTTP - 0.01 dATP - 0.01 dGTP - 0.05 UTP - 0.01 dCTP - 0.04CTP - 0.27 Palm - 0.20 Chol - - 0.28 G6P - - - 20.65 H20 - 20.70 ATP - - 0.04 GTP - 0.36 Arg - 0.05 Cys - 0.39 Glu - 0.35 Asp - 0.33 Gln - 0.28 Asn - 0.29 Ile - 0.12 His - 0.54 Gly - 0.59Lys - 0.41 Pro - 0.26 Phe - 0.15 Met - 0.55 Leu - 0.01 Trp - 0.31Thr - 0.16 Tyr - 0.35Val - 0.39 Ser - 0.51 Ala - Biomass - 20.65 Pi - 20.65ADP - 20.65 H - - - - - - H - ⁺ - - - NADH - - NAD - ⁺ - - - Gly3P - - - - GTP - - CO - ₂ - - GDP - - - - - - - - - - - - - - AKG - Iso - NADPH - - H - ⁺ - - - NADP - ⁺ - - - - - - CO - ₂ - - - - ATP - CoA - Pi - PPi - AMP - ADP - - Cit - - - Mal - Glu - - - - Asp - Fum - - - - NH - ₃ - - - - - NADPH - - H - ⁺ - - - CO - ₂ - - - NADP - ⁺ - - - - OAA - - H - ⁺ - - NADH - - NAD - ⁺ - - - - - - - - - - HO - ₂ - - - - 3PPyr - NADH - - H - ⁺ - - - NAD - ⁺ - - - - - - - CySS - - 2 GSH - GSSG - 2 Cys - - - - - H - ⁺ - - NADPH - NADP - NADH - - H - ⁺ - - NAD - - - - HO - ₂ - - - NH - ₃ - - - - Pyr - - - - - - Asn - AMP - Glu - PPi - ATP - Gln - - HO - ₂ - - - - HO - ₂ - - - NH - ₃ - - - - - Asp - - - P5C - Pro - - - - - - H - ⁺ - - NADH - - H - ⁺ - - NADPH - - NAD - ⁺ - - - NADP - ⁺ - - - GluSA - - HO - ₂ - - - - - - - - - - NH - ₃ - - Gln - - HO - ₂ - - - NH - ₃ - - ATP - - - ADP - Pi - - - - O - ₂ - - Trp - - - Lfmkynr - - - formate - - H - ⁺ - - - - - HO - ₂ - - - Glu - urcan - - - - NH - ₃ - - - His - - - - - HO - ₂ - - - - 4izp - forglu - - H - ⁺ - - 5forthf - - - H - - HO - ₂ - - - - - - THF - - Lkynr - - - anth - - H - ⁺ - - - HO - ₂ - - - - - - - - - - - - - - - 2oxoadp - - - - Thr - - - 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maps/ENGRO2_no_legend_map.svg --- a/marea_2/local/svg metabolic maps/ENGRO2_no_legend_map.svg Thu Sep 19 10:00:47 2024 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,20019 +0,0 @@ - - - - - - - - - AC - ATP - CoA - - - - - - Legend: - - = Blocked - - - - - - - - - CySS - CySS - Ala - Ala - - - - Ser - Ser - CySS - CySS - - - - - - CySS - CySS - Leu - Leu - - - - CySS - CySS - Glu - - Glu - - - Chol - - - - - - Palm - - - - - - - Ala - - Asp - - - Arg - - - - - Glu - Ser - - Gly - - - Asn - - Tyr - - Cys - - Pro - Gln - - - His - - - Leu - - - Ile - - - Lys - Met - - - Phe - - - Thr - - - Trp - - - - Val - - - - - - - - - - - - - - - - - - - - - - - - - BH4 - - - - BH2 - - - - - - - - - O - ₂ - - - - - - - - - - - - - - Pi - - - - HO - ₂ - - - - - - H - - - - - CO - ₂ - - - - - - - - - - hcarn - - - - - 4abut - - - - - anth - - - - - - Orn - Arg - - HO - ₂ - - - NH - ₃ - - Ci - Gly - - SAH - - - - Creatine - SAM - GA - - - - - - - CreatineP - ATP - ADP - - - Creatinine - - H - ⁺ - - Pi - - - - - - - - - - - - - - DHF - - - - - NADP - ⁺ - - - H - ⁺ - - NADPH - - - Folate - - - - - NADP - ⁺ - - - H - ⁺ - - NADPH - - 10formylTHF - - - H - ⁺ - - - HO - ₂ - - - - - - - - HO - ₂ - - - NADP - ⁺ - - NADPH - - CO - ₂ - - - H - ⁺ - - Formate - THF - Pi - ADP - - - - ATP - - - - - - 5,10mTHF - 5,10meTHF - - - - - NADH - - NAD - ⁺ - - - - - - - NADPH - - NADP - ⁺ - - - - - - 2 H - - NH - ₃ - - 5forthf - - - - NADPH - - 2 - H - - NADP - - 5mTHF - - - - - - Amino acids synthesis / degradation - - - - - - Pentose Phosphate pathway - - - - - - Nucleotide synthesis - - - - - - Fatty acids / Cholesterol synthesis - - - - - - Urea cycle - - - - - - Ammonia detox - - - - - - Biomass - - - - - - Fatty acids β-oxidation - - - - - - Glutathione synthesis - - - - - - Glycolysis / Gluconeogenesis - - - - Ala - AKG - Glu - - - - - - GSSG - - GSH - - - H - ⁺ - - NADH - - NAD - ⁺ - - - HO - ₂₂ - - GSH - - - 2 HO - ₂ - - GSH - - - - - NADP - ⁺ - - GSH - - - H - ⁺ - - NADPH - - - - - - - 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Glu - AKG - - - - - - ₂ - CO - - - - hcarn - ATP - AMP - PPi - His - - 2 H - ⁺ - - - - - - - - ₂ - HO - - His - - - - 4abutn - - - ₂ - HO - - - NAD - ⁺ - - - - - 4abut - - ₂ - CO - - - H - ⁺ - - NADH - - - Glu - - - - - ₂ - HO - - - ₂ - O - - - ₂₂ - HO - - - ₃ - NH - - - - - Putr - - - - - - - - spermine - - - - - spermidine - - - - - - 2obut - - - - 6Pgl - - NADP - ⁺ - - NADPH - - H - ⁺ - - 6PDG - - NADP - ⁺ - - NADPH - - CO - ₂ - - - H - ⁺ - - Ru5P - - - HO - ₂ - - - - - - - - AMP - ATP - - - R5P - - - - - Xil5P - - - - - Sed7P - GA3P - - - - F6P - Sed1,7BP - Ery4P - DHAP - ATP - ADP - - - - - - - Ery4P - - - - GA3P - F6P - Xil5P - - - - ADP - ATP - dTTP - - - - - - - - PRPP - Gly - 2 10fTHF - 2 THF - PPi - 4 ADP - Fum - 2 Gln - 2 Glu - 4 ATP - Asp - - HO - ₂ - - - CO - ₂ - - Asp - 2 ATP - - QH - ₂ - - 2 ADP - Gln - Glu - - HCO - ₃ - ⁻ - - Q - - H - ⁺ - - PPi - - CO - ₂ - - UDP - ATP - ADP - dUDP - - HO - ₂ - - - - dUMP - ADP - ATP - dTMP - 5,10meTHF - DHF - UTP - CTP - ADP - Pi - ATP - - NH - ₃ - - CDP - - HO - ₂ - - dCDP - ATP - ADP - - - - - - - - - UMP - GMP - GDP - dGDP - - 2 - HO - - AMP - ADP - ADP - ATP - - HO - ₂ - - dADP - - - - - - - - - ADP - ATP - dGTP - ADP - ATP - - - - - - - dATP - dCTP - dTDP - 4 Pi - - - IMP - 2 Pi - - - - - - - - ADP - ATP - - - - - - - ADP - ATP - - - - - - ADP - ATP - - - - - - - - - - GTP - Asp - GDP - Pi - Fum - - NAD - ⁺ - - - HO - ₂ - - ATP - - NH - ₃ - - NADH - - H - ⁺ - - AMP - PPi - - - NADP - ⁺ - - - NH - ₃ - - - H - ⁺ - - NADPH - - - - - - ADP - ATP - - - - - - - - - - - - - - - ADP - ATP - GTP - - - - - - - - - - - - - - - - - - - - ATP - - HCO - ⁻ - ₃ - - - H - ⁺ - - ADP - Pi - - - - CoA - AcACP - ACP - - - - - - CO - ₂ - - - ACP - - - - MalCoA - - CoA - MalACP - ACP - - - - AcCoA - - HO - ₂ - - CoA - AcAcCoA - - - - - PalmCoA - CoA - AMP - PPi - ATP - - - Palm - - - AcAcACP - 14 NADPH - - 14 NADP - ⁺ - - - 6 HO - ₂ - - - 6 CO - ₂ - - 6 MalACP - 7 ACP - - - 14 H - ⁺ - - - - - HMGCoA - 3 ATP - CoA - 2 NADPH - - 2 NADP - ⁺ - - 3 ADP - - CO - ₂ - - Pi - - - - - 2 PPi - fPP - 2 ippPP - ippPP - - - - - 13 NADPH - - 2 - 10 O - - - 13 NADP - ⁺ - - 2 PPi - formate - - 2 CO - ₂ - - Chol - fPP - - 15 HO - ₂ - - - - - 16 H - ⁺ - - - AcCoA - - HMGCoA - - - - - - AcCoA - CoA - - - - - - - - 3 - NH - - - - - - Ci - - - 3 - NH - - - H - ⁺ - - - ⁻ - ₃ - HCO - - 2 ADP - Pi - - - 2 ATP - - Orn - - H - ⁺ - - - Orn - - H - ⁺ - - - Ci - - CP - Pi - Orn - - - - - - - - - Pi - - H - ⁺ - - Pi - - - ATP - ADP - ATP - ADP - - - GTP - GDP - GTP - GDP - - - - - HO - ₂ - - - HO - ₂ - - - - O - ₂ - - - O - ₂ - - - - - NADH - - NAD - ⁺ - - - 0.95 QH - ₂ - - - 4.75 H - ⁺ - - 0.95 Q - - 3.8 H - ⁺ - - - FADH - ₂ - - FAD - - QH - ₂ - - Q - - 2 Cytc-ox - 2 Cytc-red - Q - - 2 H - ⁺ - - - QH - ₂ - - - - 4 H - ⁺ - - 4 Cytc-red - 4 Cytc-ox - - 2 HO - ₂ - - - 8 H - ⁺ - - - O - ₂ - - - - GSH - GSH - - - - Pi - Pi - - - - Gly - Gly - - Mal - AKG - AKG - - - - ADP - Pi - ATP - - HO - ₂ - - - 4 H - ⁺ - - 10-formylTHF - 5,10mTHF - - HO - ₂ - - 5,10meTHF - - - - NADPH - - NADP - ⁺ - - - H - ⁺ - - THF - - HO - ₂ - - - CO - ₂ - - - CO - ₂ - - - - - - NADH - NADPH - - NADP - ⁺ - - - NAD - ⁺ - - - - H - ⁺ - - - - H - ⁺ - - - - - HO - ₂₂ - - - 2 HO - ₂ - - 2 GSH - - O - ₂ - ⁻ - - - O - ₂ - ⁻ - - - 2 H - ⁺ - - - O - ₂ - - - - GSSG - - - - - NADH - - H - ⁺ - - - NAD - ⁺ - - NADPH - - H - ⁺ - - - NADP - ⁺ - - - - - - - - - CO - ₂ - - - HCO - ₃ - ⁻ - - - - H - ⁺ - - - HO - ₂ - - - - ADP - - - - Ser - Ser - - - - 0.05 O - ₂ - - - - 0.05 O - ₂ - ⁻ - - - - DHAP - DHAP - FAD - - - FADH - ₂ - - - Gly3P - Gly3P - - - - - AcCoA - Pyr - - - NAD - ⁺ - - - NADP - ⁺ - - NADH - - CO - ₂ - - - H - ⁺ - - - - - - Pi - ADP - - H - ⁺ - - ATP - - HCO - ₃ - ⁻ - - - NAD - ⁺ - - CoA - - 2 - CO - - - H - ⁺ - - NADH - - - - - - - - - NADPH - - H - ⁺ - - - CO - ₂ - - - - - - Pi - - - - - - ATP - - - - Formate - - - Formate - - Formate - - - - - - - - - - H - ⁺ - - - H - ⁺ - - - H - ⁺ - - Mal - - H - ⁺ - - - OAA - Cit - Isocit - AKG - - NADP - ⁺ - - SuCoA - Succ - Fum - Mal - - FAD - - FADH - ₂ - - - NAD - ⁺ - - - - HO - ₂ - - CoA - - - - - HO - ₂ - - - - - - - - NADH - - H - ⁺ - - - - - GDP - Pi - CoA - GTP - - - - - CoA - - NAD - ⁺ - - - - NADH - - CO - ₂ - - - H - ⁺ - - - - NADPH - ⁺ - - - CO - ₂ - - - H - ⁺ - - - - - - NAD - ⁺ - - - NADH - ⁺ - - - H - ⁺ - - - CO - ₂ - - - - - - - - - - - - - - - - - NADH - - H - ⁺ - - - NH - ₃ - - - NAD - ⁺ - - - HO - ₂ - - NADPH - - H - ⁺ - - - NH - ₃ - - - NADP - ⁺ - - - HO - ₂ - - - - - - - - - - NADP - ⁺ - - NADPH - - H - ⁺ - - DHF - - - - - NADP - ⁺ - - NADPH - - H - ⁺ - - Folate - - - - - 4 H - ⁺ - - - 4 H - ⁺ - - - NADH - - H - ⁺ - - - HO - ₂ - - - NAD - ⁺ - - - - - Gln - Glu - - - Gln - - - - NH - ₃ - - Glu - - HO - ₂ - - - - - H - ⁺ - - - H - ⁺ - - - H - ⁺ - - - H - ⁺ - - - Folate - - - - + - H - - Mal - - Fum - - - - Pi - Pi - Fum - - - GluSA - - - - GluSA - - - - - - - - - - - - - - - - - Val, 3mob, propCoA - - - Leu - Leu - - - - - - Val - Val - - - - - - - - - H - ⁺ - - - H - ⁺ - - Lys - Lys - - - 3mob - 3mob - - H - ⁺ - - - H - ⁺ - - - - - - 4mop - 4mop - - H - ⁺ - - - H - ⁺ - - - - - - 2oxoadp - 2oxoadp - - AKG - AKG - - - propCoA - propCoA - - - - - - 5,10meTHF - 5,10meTHF - - - - - - AKG - Glu - - - - - - - Asp - Glu - - H - ⁺ - - - H - ⁺ - - Glu - - - - - AcAcCoA - - - CoA - 2 AcCoA - - - - NADH - - NAD - ⁺ - - - H - ⁺ - - - - - - - - - - - - - - - - - - - - - - - - HMGCoA - Leu, 4mop - Lys, 2oxoadp - - AcCoA - - HO - ₂ - - CoA - - H - ⁺ - - - - HO - ₂ - - - - - - - - - - - - - - Ci - Orn - ArgSuc - Arg - Fum - - - HO - ₂ - - - Urea - - - - - - - - - 3 - NH - - - - - PalmCarn - PalmCarn - - - - Carn - Carn - PalmCoA - - - - Carn - CoA - 8 AcCoA - 7 FAD - - 7 NAD - ⁺ - - 7 CoA - - 7 HO - ₂ - - - - 7 FADH - ₂ - - 7 NADH - - 7 H - ⁺ - - - - - - H - ⁺ - - - CO - ₂ - - - HCO - ₃ - ⁻ - - - - HO - ₂ - - - ADP - Pi - - HO - ₂ - - ATP - - - - H - ⁺ - - PPi - Pi - Pi - - HO - ₂ - - - - - - 0.01 dTTP - 0.01 dATP - 0.01 dGTP - 0.05 UTP - 0.01 dCTP - 0.04CTP - 0.27 Palm - 0.20 Chol - - 0.28 G6P - - - 20.65 H20 - 20.70 ATP - - 0.04 GTP - 0.36 Arg - 0.05 Cys - 0.39 Glu - 0.35 Asp - 0.33 Gln - 0.28 Asn - 0.29 Ile - 0.12 His - 0.54 Gly - 0.59Lys - 0.41 Pro - 0.26 Phe - 0.15 Met - 0.55 Leu - 0.01 Trp - 0.31Thr - 0.16 Tyr - 0.35Val - 0.39 Ser - 0.51 Ala - Biomass - 20.65 Pi - 20.65ADP - 20.65 H - - - - - - H - ⁺ - - - NADH - - NAD - ⁺ - - - Gly3P - - - - GTP - - CO - ₂ - - GDP - - - - - - - - - - - - - - AKG - Iso - NADPH - - H - ⁺ - - - NADP - ⁺ - - - - - - CO - ₂ - - - - ATP - CoA - Pi - PPi - AMP - ADP - - Cit - - - Mal - Glu - - - - Asp - Fum - - - - NH - ₃ - - - - - NADPH - - H - ⁺ - - - CO - ₂ - - - NADP - ⁺ - - - - OAA - - H - ⁺ - - NADH - - NAD - ⁺ - - - - - - - - - - HO - ₂ - - - - 3PPyr - NADH - - H - ⁺ - - - NAD - ⁺ - - - - - - - CySS - - 2 GSH - GSSG - 2 Cys - - - - - H - ⁺ - - NADPH - NADP - NADH - - H - ⁺ - - NAD - - - - HO - ₂ - - - NH - ₃ - - - - Pyr - - - - - - Asn - AMP - Glu - PPi - ATP - Gln - - HO - ₂ - - - - HO - ₂ - - - NH - ₃ - - - - - Asp - - - P5C - Pro - - - - - - H - ⁺ - - NADH - - H - ⁺ - - NADPH - - NAD - ⁺ - - - NADP - ⁺ - - - GluSA - - HO - ₂ - - - - - - - - - - NH - ₃ - - Gln - - HO - ₂ - - - NH - ₃ - - ATP - - - ADP - Pi - - - - O - ₂ - - Trp - - - Lfmkynr - - - formate - - H - ⁺ - - - - - HO - ₂ - - - Glu - urcan - - - - NH - ₃ - - - His - - - - - HO - ₂ - - - - 4izp - forglu - - H - ⁺ - - 5forthf - - - H - - HO - ₂ - - - - - - THF - - Lkynr - - - anth - - H - ⁺ - - - HO - ₂ - - - - - - - - - - - - - - - 2oxoadp - - - - Thr - - - NH - ₃ - - - - - - - - - - - - - - - - 2obut - propCoA - - - CoA - NAD - NADH - - CO - ₂ - - - - - hgentis - - hpp - - - O - ₂ - - - CO - ₂ - - - - - 4mlacac - - - O - ₂ - - - H - ⁺ - - - - - - 4fumacac - - - - - - HO - ₂ - - - H - ⁺ - - Fum - AcAc - - - - - CoA - ATP - PPi - AMP - AcAcCoA - - - - Tyr - - - - AKG - Glu - - - Phe - - - - - - - BH4 - BH2 - - HO - ₂ - - - O - ₂ - - - - - 3mob - - Val - - Glu - AKG - - - - - - - - - - - - - - - 4mop - - Leu - - Glu - AKG - - - - - - - - - - - - - - - Cyst - Cys - - - NH - ₃ - - 2-obut - - HO - ₂ - - - - - - - - HO - ₂ - - Hcys - - - Gly - THF - - HO - ₂ - - 5,10meTHF - - - - - - HO - ₂ - - Pi - - - - - Ser - - NH - ₃ - - - - - - - - - 3PSer - Glu - AKG - - - - - - diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/svg metabolic maps/HMRcore_map.svg diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/local/svg metabolic maps/HMRcore_no_legend_map.svg --- a/marea_2/local/svg metabolic maps/HMRcore_no_legend_map.svg Thu Sep 19 10:00:47 2024 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,7654 +0,0 @@ - - - -image/svg+xml= Blocked -Legend - - -F6P -F16BP -GA3P -1,3BPGA -3PG -2PG -PEP -Pyr -Lact -ATP -ADP -NAD -+ -Pi -NADH+H -ADP -ATP -ADP -ATP -DHAP -H -2 -O -NAD -6Pgl -NADP -6PDG -NADP -Ru5P -R5P -AMP -ATP -H -2 -O -Xil5P -Sed7P -GA3P -Ery4P -F6P -GA3P -F6P -Xil5P -Sed1,7BP -ATP -ADP -Ery4P -DHAP -PRPP -Gly -2 10-forTHF -2 THF -PPi -4 ADP -Fum -IMP -2 Gln -2 Glu -4 ATP -H -2 -O -CO -2 -GDP -ATP -ADP -ATP -ADP -CoA -AcCoA -OAA -ippPP -fPP -Chol -ATP -HCO -3 -- -H -ADP -Pi -MalCoA -CO -2 -AcAcACP -14NADPH -14NADP -6 H -2 -O -6 CO -2 -Palm -6 MalACP -7 ACP -CoA -MalACP -ACP -CoA -AcACP -ACP -ACP -H -Pi -H -Pi -ATP -ADP -ATP -ADP -GTP -GDP -GTP -GDP -H -2 -O -H -2 -O -O -2 -O -2 -CO -2 -CO -2 -CoA -CoA -NH -3 -NH -3 -AKG -AKG -Pi -OAA -AcCoA -Cit -Isocit -AKG -NADP -NADPH -NAD -NADH -SuCoA -Succ -Fum -Mal -NAD -+ -CoA -GDP -+ -Pi -GTP -+ -CoA -FAD -FADH -2 -NAD -Pyr -H -2 -O -CoA -CO -2 -CO -2 -H -2 -O -Fum -Fum -Pi -Pi -H -H -NAD -QH -2 -5 H -2 Cytc-ox -2 Cytc-red -Q -2H -QH -2 -4 H -4 Cytc-red -4 Cytc-ox -2H -2 -O -8H -O -2 -4 H -CO -2 -HCO -3 -- -H -H -2 -O -Glc -H -2 -O -O -2 -Gln -NH -3 -Folate -Urea -Putr -Lact -H -Glu -Arg -CO -2 -Pi -GA -Asp -2 ATP -QH -2 -2 ADP -UMP -Gln -Glu -HCO -3 -- -Q -H -PPi -UDP -ATP -ADP -dUDP -H -2 -O -dUMP -ADP -ATP -CO -2 -dTMP -meTHF -DHF -UTP -CTP -ADP+Pi -ATP+NH -3 -ATP -ADP -CDP -CMP -H -2 -O -dCDP -3PPyr -NADH -+ -H -NAD -3PSer -Glu -AKG -Ser -H -2 -O -Pi -Gly -THF -Pyr -NH -3 -DHF -Folate -NADP -NADPH -+H -THF -NADP -NADPH -+H -10-formyl -THF -ADP -+ -Pi -for+ATP -NADP -+ -H -2 -O -NADPH+ -H+CO -2 -mTHF -H -meTHF -NADPH -NADP -DHF -Folate -NADP -NADPH+H -THF -NADP -NADPH+H -10-formylTHF -mTHF -H -2 -O -meTHF -NADPH -NADP -OAA -Gln -Glu -NH -3 -H -2 -O -ATP -ADP -NH -3 -Pi -H -H -H -H -Gln -Glu -NH -3 -H -2 -O -NH -3 -Orn -Ci -Ci -ArgSuc -Arg -Orn -Asp -+ -ATP -AMP -+ -PPi -Fum -H -2 -O -Urea -H -Orn -Putr -CO -2 -GluSA -AKG -Glu -GluSA -P5C -H -2 -O -NADH+H -NAD -Pro -NADPH+H -NADP -NADH -+ -H -NAD+H -2 -O -Glu -NAD -+ -H -2 -O -NADH+ -H+NH -3 -NADP -+ -H -2 -O -NADPH+ -H+NH -3 -Ser -Gly -THF -Asp -Asp -H -Glu -H -Glu -Ser -Ser -Gly -Gly -Folate -Folate -Formate -Formate -ATP -H -Orn -H -PPi -Pi -Pi -H -2 -O -CO -2 -HCO -3 -- -H -H -2 -O -Orn -Arg -H -2 -O -NH -3 -Ci -Asn -Glu -+ -AMP -+ -PPi -Gln+ATP+H -2 -O -H -2 -O -NH -3 -Fum -Mal -H -2 -O -OAA -GTP -GDP+CO -2 -Iso -NADPH -AKG -NADP -CO -2 -Fum -NH -3 -Ala -AKG -Glu -Biomass -NADPH+ -H+CO2 -NADPH -+H -NADH -+ -H -NAD -CoA -CO -2 -NADH -H -Mal -Mal -Cit -2 Pi -4 Pi -Pi -CoA -3ADP -2 NADP -Pi -CO2 -2 NADPH -2 H -3 ATP -2 ippPP -2 PPi -fPP -15 H -2 -O -2 PPi -13 NADP -for -2 CO -2 -13 NADPH -16 H -10 O -2 -14 H -ADP -Pi -ATP -HCO -3 -- -H -H -H -NADH -+ -H -+ -CO -2 -NADH+H -NAD -NADH -H -CO -2 -NADP -NADPH -H -CO -2 -H -NAD -NADH -+ -H -Q -NADH -4 H -ADP -ATP -2 H -2 -O -Pi -4 H -4 H -AKG -AKG -Mal -Mal -HCO -3 -- -2 ATP -H -2 ADP -Pi -Pi -H -2 -O -Glu -AKG -Glu -AKG -Asp -AMP -GTP -Asp -Fum -GDP -GMP -NAD -H -2 -O -NADH -H -AMP -ATP -NH -3 -PPi -NADPH -H -NADP -NH -3 -H -2 -O -dGDP -ADP -ATP -ADP -H -2 -O -dADP -ATP -ADP -ADP -G6P -Glc -CoA -AcCoA -AcAcCoA -H -2 -O -AcCoA -CoA -HMGCoA -Pi -ADP -ATP -dGMP -ATP -ADP -dCMP -ATP -ADP -H -2 -O -NADH -NAD -CP -Gly -GA -H -2 -O -formate+ATP -ADP+Pi -AMP+PPi -ATP+CoA -Palm -PalmCoA -CoA -carnitine -PalmCarnitine -carnitine -carnitine -PalmCarnitine -CoA -carnitine -PalmCoA -7 CoA -7 NAD -7 FAD -7 H -2 -O -7 NADH -7 FADH -2 -7 H -8 AcCoA -ATP -ADP -Pi -Orn -H -H -Orn -Orn -Orn -H -H -Arg -Arg -Orn -Orn -H -H -Arg -Arg -Ci -Ci -H -H -Arg -Arg -H -H -Arg -Arg -Ci -Ci -Arg -H -H -Arg -Ci -H -H -Ci -10-formylTHF -carnitine -Palm -ATP -ADP -dAMP -H -2 -O -Pi -H -2 -O -Pi -Cit -TITOLO: TITOLOTITOLO Fold Changemin: max: \ No newline at end of file diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/marea.py --- a/marea_2/marea.py Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/marea.py Wed Nov 06 18:02:22 2024 +0000 @@ -15,11 +15,12 @@ import argparse import pyvips from typing import Tuple, Union, Optional, List, Dict +import copy ERRORS = [] ########################## argparse ########################################## ARGS :argparse.Namespace -def process_args() -> argparse.Namespace: +def process_args(args:List[str] = None) -> argparse.Namespace: """ Interfaces the script of a module with its frontend, making the user's choices for various parameters available as values in code. @@ -146,11 +147,17 @@ help='custom map to use') parser.add_argument( + '-idop', '--output_path', + type = str, + default='result', + help = 'output path for maps') + + parser.add_argument( '-mc', '--choice_map', type = utils.Model, default = utils.Model.HMRcore, choices = [utils.Model.HMRcore, utils.Model.ENGRO2, utils.Model.Custom]) - args :argparse.Namespace = parser.parse_args() + args :argparse.Namespace = parser.parse_args(args) if args.using_RAS and not args.using_RPS: args.net = False return args @@ -650,7 +657,7 @@ # all output files: I don't care, this was never the performance bottleneck of the tool and # there is no other net gain in saving and re-using the built string. ext, - prefix = "result") + prefix = ARGS.output_path) FIELD_NOT_AVAILABLE = '/' def writeToCsv(rows: List[list], fieldNames :List[str], outPath :utils.FilePath) -> None: @@ -761,7 +768,7 @@ return tmp, max_z_score -def computeEnrichment(metabMap :ET.ElementTree, class_pat :Dict[str, List[List[float]]], ids :List[str], *, fromRAS = True) -> None: +def computeEnrichment(metabMap: ET.ElementTree, class_pat: Dict[str, List[List[float]]], ids: List[str], *, fromRAS=True) -> List[Tuple[str, str, dict, float]]: """ Compares clustered data based on a given comparison mode and applies enrichment-based styling on the provided metabolic map. @@ -773,58 +780,52 @@ fromRAS : whether the data to enrich consists of RAS scores. Returns: - None - + List[Tuple[str, str, dict, float]]: List of tuples with pairs of dataset names, comparison dictionary, and max z-score. + Raises: sys.exit : if there are less than 2 classes for comparison Side effects: - metabMap : mut - ids : mut + metabMap : mutates based on calculated enrichment """ - class_pat = { k.strip() : v for k, v in class_pat.items() } - #TODO: simplfy this stuff vvv and stop using sys.exit (raise the correct utils error) - if (not class_pat) or (len(class_pat.keys()) < 2): sys.exit('Execution aborted: classes provided for comparisons are less than two\n') + class_pat = {k.strip(): v for k, v in class_pat.items()} + if (not class_pat) or (len(class_pat.keys()) < 2): + sys.exit('Execution aborted: classes provided for comparisons are less than two\n') + + enrichment_results = [] if ARGS.comparison == "manyvsmany": for i, j in it.combinations(class_pat.keys(), 2): - #TODO: these 2 functions are always called in pair and in this order and need common data, - # some clever refactoring would be appreciated. comparisonDict, max_z_score = compareDatasetPair(class_pat.get(i), class_pat.get(j), ids) - temp_thingsInCommon(comparisonDict, metabMap, max_z_score, i, j, fromRAS) + enrichment_results.append((i, j, comparisonDict, max_z_score)) elif ARGS.comparison == "onevsrest": for single_cluster in class_pat.keys(): - t :List[List[List[float]]] = [] - for k in class_pat.keys(): - if k != single_cluster: - t.append(class_pat.get(k)) - - rest :List[List[float]] = [] - for i in t: - rest = rest + i - + rest = [item for k, v in class_pat.items() if k != single_cluster for item in v] comparisonDict, max_z_score = compareDatasetPair(class_pat.get(single_cluster), rest, ids) - temp_thingsInCommon(comparisonDict, metabMap, max_z_score, single_cluster, fromRAS) + enrichment_results.append((single_cluster, "rest", comparisonDict, max_z_score)) elif ARGS.comparison == "onevsmany": controlItems = class_pat.get(ARGS.control) for otherDataset in class_pat.keys(): - if otherDataset == ARGS.control: continue - + if otherDataset == ARGS.control: + continue comparisonDict, max_z_score = compareDatasetPair(controlItems, class_pat.get(otherDataset), ids) - temp_thingsInCommon(comparisonDict, metabMap, max_z_score, ARGS.control, otherDataset, fromRAS) + enrichment_results.append((ARGS.control, otherDataset, comparisonDict, max_z_score)) + + return enrichment_results -def createOutputMaps(dataset1Name :str, dataset2Name :str, core_map :ET.ElementTree) -> None: - svgFilePath = buildOutputPath(dataset1Name, dataset2Name, details = "SVG Map", ext = utils.FileFormat.SVG) +def createOutputMaps(dataset1Name: str, dataset2Name: str, core_map: ET.ElementTree) -> None: + svgFilePath = buildOutputPath(dataset1Name, dataset2Name, details="SVG Map", ext=utils.FileFormat.SVG) utils.writeSvg(svgFilePath, core_map) if ARGS.generate_pdf: - pngPath = buildOutputPath(dataset1Name, dataset2Name, details = "PNG Map", ext = utils.FileFormat.PNG) - pdfPath = buildOutputPath(dataset1Name, dataset2Name, details = "PDF Map", ext = utils.FileFormat.PDF) - convert_to_pdf(svgFilePath, pngPath, pdfPath) + pngPath = buildOutputPath(dataset1Name, dataset2Name, details="PNG Map", ext=utils.FileFormat.PNG) + pdfPath = buildOutputPath(dataset1Name, dataset2Name, details="PDF Map", ext=utils.FileFormat.PDF) + convert_to_pdf(svgFilePath, pngPath, pdfPath) - if not ARGS.generate_svg: os.remove(svgFilePath.show()) + if not ARGS.generate_svg: + os.remove(svgFilePath.show()) ClassPat = Dict[str, List[List[float]]] def getClassesAndIdsFromDatasets(datasetsPaths :List[str], datasetPath :str, classPath :str, names :List[str]) -> Tuple[List[str], ClassPat]: @@ -870,7 +871,7 @@ return { id : list(map(utils.Float("Dataset values, not an argument"), values)) for id, values in dataset.items() }, IDs ############################ MAIN ############################################# -def main() -> None: +def main(args:List[str] = None) -> None: """ Initializes everything and sets the program in motion based on the fronted input arguments. @@ -880,46 +881,33 @@ Raises: sys.exit : if a user-provided custom map is in the wrong format (ET.XMLSyntaxError, ET.XMLSchemaParseError) """ - global ARGS - ARGS = process_args() + ARGS = process_args(args) - if os.path.isdir('result') == False: os.makedirs('result') + if not os.path.isdir(ARGS.output_path): + os.makedirs(ARGS.output_path) - core_map :ET.ElementTree = ARGS.choice_map.getMap( + core_map: ET.ElementTree = ARGS.choice_map.getMap( ARGS.tool_dir, utils.FilePath.fromStrPath(ARGS.custom_map) if ARGS.custom_map else None) - # TODO: ^^^ ugly but fine for now, the argument is None if the model isn't custom because no file was given. - # getMap will None-check the customPath and panic when the model IS custom but there's no file (good). A cleaner - # solution can be derived from my comment in FilePath.fromStrPath - + if ARGS.using_RAS: ids, class_pat = getClassesAndIdsFromDatasets(ARGS.input_datas, ARGS.input_data, ARGS.input_class, ARGS.names) - computeEnrichment(core_map, class_pat, ids) + enrichment_results = computeEnrichment(core_map, class_pat, ids) + for i, j, comparisonDict, max_z_score in enrichment_results: + map_copy = copy.deepcopy(core_map) + temp_thingsInCommon(comparisonDict, map_copy, max_z_score, i, j, ras_enrichment=True) + createOutputMaps(i, j, map_copy) if ARGS.using_RPS: ids, class_pat = getClassesAndIdsFromDatasets(ARGS.input_datas_rps, ARGS.input_data_rps, ARGS.input_class_rps, ARGS.names_rps) - computeEnrichment(core_map, class_pat, ids, fromRAS = False) - - # create output files: TODO: this is the same comparison happening in "maps", find a better way to organize this - if ARGS.comparison == "manyvsmany": - for i, j in it.combinations(class_pat.keys(), 2): createOutputMaps(i, j, core_map) - return - - if ARGS.comparison == "onevsrest": - for single_cluster in class_pat.keys(): createOutputMaps(single_cluster, "rest", core_map) - return - - for otherDataset in class_pat.keys(): - if otherDataset != ARGS.control: createOutputMaps(i, j, core_map) + enrichment_results = computeEnrichment(core_map, class_pat, ids, fromRAS=False) + for i, j, comparisonDict, max_z_score in enrichment_results: + map_copy = copy.deepcopy(core_map) + temp_thingsInCommon(comparisonDict, map_copy, max_z_score, i, j, ras_enrichment=False) + createOutputMaps(i, j, map_copy) - if not ERRORS: return - utils.logWarning( - f"The following reaction IDs were mentioned in the dataset but weren't found in the map: {ERRORS}", - ARGS.out_log) - - print('Execution succeded') - + print('Execution succeeded') ############################################################################### if __name__ == "__main__": main() \ No newline at end of file diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/marea.xml --- a/marea_2/marea.xml Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/marea.xml Wed Nov 06 18:02:22 2024 +0000 @@ -307,11 +307,11 @@ .. class:: infomark -**TIP**: If your dataset is not split into classes, use `MaREA cluster analysis`_. +**TIP**: If your dataset is not split into classes, use MaREA cluster analysis. .. class:: infomark -**TIP**: This tool using the RAS scores computed by `Ras tool`_. +**TIP**: This tool using the RAS scores computed by Ras generator tool. @REFERENCE@ diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/marea_cluster.py --- a/marea_2/marea_cluster.py Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/marea_cluster.py Wed Nov 06 18:02:22 2024 +0000 @@ -20,7 +20,7 @@ from typing import Optional, Dict, List ################################# process args ############################### -def process_args(args :List[str]) -> argparse.Namespace: +def process_args(args :List[str] = None) -> argparse.Namespace: """ Processes command-line arguments. @@ -86,9 +86,13 @@ type = str, help = 'output of best cluster tsv') - + parser.add_argument( + '-idop', '--output_path', + type = str, + default='result', + help = 'output path for maps') - args = parser.parse_args() + args = parser.parse_args(args) return args ########################### warning ########################################### @@ -217,8 +221,8 @@ Returns: None """ - if not os.path.exists('clustering'): - os.makedirs('clustering') + if not os.path.exists(args.output_path): + os.makedirs(args.output_path) if elbow == 'true': @@ -259,7 +263,7 @@ if (i + k_min == best): prefix = '_BEST' - write_to_csv(dataset, all_labels[i], 'clustering/kmeans_with_' + str(i + k_min) + prefix + '_clusters.tsv') + write_to_csv(dataset, all_labels[i], f'{args.output_path}/kmeans_with_' + str(i + k_min) + prefix + '_clusters.tsv') if (prefix == '_BEST'): @@ -272,7 +276,7 @@ if silhouette: - silhouette_draw(dataset, all_labels[i], i + k_min, 'clustering/silhouette_with_' + str(i + k_min) + prefix + '_clusters.png') + silhouette_draw(dataset, all_labels[i], i + k_min, f'{args.output_path}/silhouette_with_' + str(i + k_min) + prefix + '_clusters.png') if elbow: @@ -303,7 +307,7 @@ plt.plot(x, distortions, marker = 'o') plt.xlabel('Number of clusters (k)') plt.ylabel('Distortion') - s = 'clustering/elbow_plot.png' + s = f'{args.output_path}/elbow_plot.png' fig = plt.gcf() fig.set_size_inches(18.5, 10.5, forward = True) fig.savefig(s, dpi=100) @@ -406,8 +410,8 @@ Returns: None """ - if not os.path.exists('clustering'): - os.makedirs('clustering') + if not os.path.exists(args.output_path): + os.makedirs(args.output_path) if eps is not None: clusterer = DBSCAN(eps = eps, min_samples = min_samples) @@ -445,14 +449,14 @@ Returns: None """ - if not os.path.exists('clustering'): - os.makedirs('clustering') + if not os.path.exists(args.output_path): + os.makedirs(args.output_path) plt.figure(figsize=(10, 7)) plt.title("Customer Dendograms") shc.dendrogram(shc.linkage(dataset, method='ward'), labels=dataset.index.values.tolist()) fig = plt.gcf() - fig.savefig('clustering/dendogram.png', dpi=200) + fig.savefig(f'{args.output_path}/dendogram.png', dpi=200) range_n_clusters = [i for i in range(k_min, k_max+1)] @@ -466,7 +470,7 @@ cluster.fit_predict(dataset) cluster_labels = cluster.labels_ labels.append(cluster_labels) - write_to_csv(dataset, cluster_labels, 'clustering/hierarchical_with_' + str(n_clusters) + '_clusters.tsv') + write_to_csv(dataset, cluster_labels, f'{args.output_path}/hierarchical_with_' + str(n_clusters) + '_clusters.tsv') best = max_index(scores) + k_min @@ -475,7 +479,7 @@ if (i + k_min == best): prefix = '_BEST' if silhouette == 'true': - silhouette_draw(dataset, labels[i], i + k_min, 'clustering/silhouette_with_' + str(i + k_min) + prefix + '_clusters.png') + silhouette_draw(dataset, labels[i], i + k_min, f'{args.output_path}/silhouette_with_' + str(i + k_min) + prefix + '_clusters.png') for i in range(len(labels)): if (i + k_min == best): @@ -486,17 +490,18 @@ ############################# main ########################################### -def main() -> None: +def main(args_in:List[str] = None) -> None: """ Initializes everything and sets the program in motion based on the fronted input arguments. Returns: None """ - if not os.path.exists('clustering'): - os.makedirs('clustering') + global args + args = process_args(args_in) - args = process_args(sys.argv) + if not os.path.exists(args.output_path): + os.makedirs(args.output_path) #Data read diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/marea_cluster.xml diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/marea_macros.xml --- a/marea_2/marea_macros.xml Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/marea_macros.xml Wed Nov 06 18:02:22 2024 +0000 @@ -140,7 +140,56 @@ url = {https://doi.org/10.1016/j.csbj.2020.04.008}, } + + @article{ebrahim2013cobrapy, + title={COBRApy: constraints-based reconstruction and analysis for python}, + author={Ebrahim, Ali and Lerman, Joshua A and Palsson, Bernhard O and Hyduke, Daniel R}, + journal={BMC systems biology}, + volume={7}, + pages={1--6}, + year={2013}, + publisher={Springer} + } + + + + + @article{galuzzi2024adjusting, + title={Adjusting for false discoveries in constraint-based differential metabolic flux analysis}, + author={Galuzzi, Bruno G and Milazzo, Luca and Damiani, Chiara}, + journal={Journal of Biomedical Informatics}, + volume={150}, + pages={104597}, + year={2024}, + publisher={Elsevier} + } + + + @inproceedings{galuzzi2022best, + title={Best practices in flux sampling of constrained-based models}, + author={Galuzzi, Bruno G and Milazzo, Luca and Damiani, Chiara}, + booktitle={International Conference on Machine Learning, Optimization, and Data Science}, + pages={234--248}, + year={2022}, + organization={Springer} + } + + + @article{ebrahim2013cobrapy, + title={COBRApy: constraints-based reconstruction and analysis for python}, + author={Ebrahim, Ali and Lerman, Joshua A and Palsson, Bernhard O and Hyduke, Daniel R}, + journal={BMC systems biology}, + volume={7}, + pages={1--6}, + year={2013}, + publisher={Springer} + } + + + + + diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/ras_generator.py --- a/marea_2/ras_generator.py Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/ras_generator.py Wed Nov 06 18:02:22 2024 +0000 @@ -12,7 +12,7 @@ ERRORS = [] ########################## argparse ########################################## ARGS :argparse.Namespace -def process_args() -> argparse.Namespace: +def process_args(args:List[str] = None) -> argparse.Namespace: """ Processes command-line arguments. @@ -61,8 +61,9 @@ '-ra', '--ras_output', type = str, required = True, help = 'ras output') + - return parser.parse_args() + return parser.parse_args(args) ############################ dataset input #################################### def read_dataset(data :str, name :str) -> pd.DataFrame: @@ -231,7 +232,9 @@ elif args.rules_selector == 'ENGRO2': gene_in_rule = pk.load(open(args.tool_dir + '/local/pickle files/ENGRO2_genes.p', 'rb')) - + print(f"{args.tool_dir}'/local/pickle files/ENGRO2_genes.p'") + utils.logWarning(f"{args.tool_dir}'/local/pickle files/ENGRO2_genes.p'", ARGS.out_log) + print(args.rules_selector) gene_in_rule = gene_in_rule.get(type_gene) else: @@ -645,7 +648,7 @@ # csv rules need to be parsed, those in a pickle format are taken to be pre-parsed. return { line[0] : ruleUtils.parseRuleToNestedList(line[1]) for line in utils.readCsv(datFilePath) } -def main() -> None: +def main(args:List[str] = None) -> None: """ Initializes everything and sets the program in motion based on the fronted input arguments. @@ -654,8 +657,8 @@ """ # get args from frontend (related xml) global ARGS - ARGS = process_args() - + ARGS = process_args(args) + print(ARGS.rules_selector) # read dataset dataset = read_dataset(ARGS.input, "dataset") dataset.iloc[:, 0] = (dataset.iloc[:, 0]).astype(str) diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/ras_generator.xml --- a/marea_2/ras_generator.xml Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/ras_generator.xml Wed Nov 06 18:02:22 2024 +0000 @@ -32,13 +32,13 @@ - + - + diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/rps_generator.py --- a/marea_2/rps_generator.py Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/rps_generator.py Wed Nov 06 18:02:22 2024 +0000 @@ -16,7 +16,7 @@ ########################## argparse ########################################## ARGS :argparse.Namespace -def process_args() -> argparse.Namespace: +def process_args(args:List[str] = None) -> argparse.Namespace: """ Processes command-line arguments. @@ -51,7 +51,7 @@ required = True, help = 'rps output') - args = parser.parse_args() + args = parser.parse_args(args) return args ############################ dataset name ##################################### @@ -222,7 +222,7 @@ df.to_csv(ARGS.rps_output, sep = '\t', na_rep = "None", index = False) ############################ main #################################### -def main() -> None: +def main(args:List[str] = None) -> None: """ Initializes everything and sets the program in motion based on the fronted input arguments. @@ -230,7 +230,7 @@ None """ global ARGS - ARGS = process_args() + ARGS = process_args(args) # TODO:use utils functions vvv with open(ARGS.tool_dir + '/local/pickle files/black_list.pickle', 'rb') as bl: diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/rps_generator.xml --- a/marea_2/rps_generator.xml Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/rps_generator.xml Wed Nov 06 18:02:22 2024 +0000 @@ -24,7 +24,7 @@ - + @@ -39,7 +39,7 @@ - + diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/testing.py --- a/marea_2/testing.py Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/testing.py Wed Nov 06 18:02:22 2024 +0000 @@ -1,4 +1,4 @@ -# This is a general-purpose "testing utilities" module for the MaREA tool. +# This is a general-purpose "testing utilities" module for the COBRAxy tool. # This code was written entirely by m.ferrari133@campus.unimib.it and then (hopefully) many # more people contributed by writing tests for this tool's modules, feel free to send an email for # any questions. @@ -495,8 +495,8 @@ # ^^^ Manually applied an extra newline of space. ## Unit testing all the modules: -def unit_marea() -> None: - import marea as m +def unit_cobraxy() -> None: + import cobraxy as m import math import lxml.etree as ET import utils.general_utils as utils @@ -521,7 +521,7 @@ [math.nan, math.nan, math.nan, math.nan, math.nan, math.nan, math.nan]] } - unitTester = UnitTester("marea", LogMode.Pedantic, False, + unitTester = UnitTester("cobraxy", LogMode.Pedantic, False, UnitTest(m.name_dataset, ["customName", 12], ExactValue("customName")), UnitTest(m.name_dataset, ["Dataset", 12], ExactValue("Dataset_12")), @@ -800,7 +800,7 @@ ).testModule() if __name__ == "__main__": - unit_marea() + unit_cobraxy() unit_custom_data_generator() unit_utils() unit_ras_generator() \ No newline at end of file diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/utils/custom_data_generator.py --- a/marea_2/utils/custom_data_generator.py Thu Sep 19 10:00:47 2024 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,218 +0,0 @@ -import os -import csv -import cobra -import pickle -import argparse -import pandas as pd -import utils.general_utils as utils -import utils.rule_parsing as rulesUtils -from typing import Optional, Tuple, Union, Dict -import utils.reaction_parsing as reactionUtils - -ARGS : argparse.Namespace -def process_args() -> argparse.Namespace: - """ - Interfaces the script of a module with its frontend, making the user's choices for - various parameters available as values in code. - - Args: - args : Always obtained (in file) from sys.argv - - Returns: - Namespace : An object containing the parsed arguments - """ - parser = argparse.ArgumentParser( - usage = "%(prog)s [options]", - description = "generate custom data from a given model") - - parser.add_argument("-ol", "--out_log", type = str, required = True, help = "Output log") - - parser.add_argument("-orules", "--out_rules", type = str, required = True, help = "Output rules") - parser.add_argument("-orxns", "--out_reactions", type = str, required = True, help = "Output reactions") - parser.add_argument("-omedium", "--out_medium", type = str, required = True, help = "Output medium") - parser.add_argument("-obnds", "--out_bounds", type = str, required = True, help = "Output bounds") - - parser.add_argument("-id", "--input", type = str, required = True, help = "Input model") - parser.add_argument("-mn", "--name", type = str, required = True, help = "Input model name") - # ^ I need this because galaxy converts my files into .dat but I need to know what extension they were in - - argsNamespace = parser.parse_args() - argsNamespace.out_dir = "result" - # ^ can't get this one to work from xml, there doesn't seem to be a way to get the directory attribute from the collection - - return argsNamespace - -################################- INPUT DATA LOADING -################################ -def load_custom_model(file_path :utils.FilePath, ext :Optional[utils.FileFormat] = None) -> cobra.Model: - """ - Loads a custom model from a file, either in JSON or XML format. - - Args: - file_path : The path to the file containing the custom model. - ext : explicit file extension. Necessary for standard use in galaxy because of its weird behaviour. - - Raises: - DataErr : if the file is in an invalid format or cannot be opened for whatever reason. - - Returns: - cobra.Model : the model, if successfully opened. - """ - ext = ext if ext else file_path.ext - try: - if ext is utils.FileFormat.XML: - return cobra.io.read_sbml_model(file_path.show()) - - if ext is utils.FileFormat.JSON: - return cobra.io.load_json_model(file_path.show()) - - except Exception as e: raise utils.DataErr(file_path, e.__str__()) - raise utils.DataErr(file_path, - f"Formato \"{file_path.ext}\" non riconosciuto, sono supportati solo file JSON e XML") - -################################- DATA GENERATION -################################ -ReactionId = str -def generate_rules(model: cobra.Model, *, asParsed = True) -> Union[Dict[ReactionId, rulesUtils.OpList], Dict[ReactionId, str]]: - """ - Generates a dictionary mapping reaction ids to rules from the model. - - Args: - model : the model to derive data from. - asParsed : if True parses the rules to an optimized runtime format, otherwise leaves them as strings. - - Returns: - Dict[ReactionId, rulesUtils.OpList] : the generated dictionary of parsed rules. - Dict[ReactionId, str] : the generated dictionary of raw rules. - """ - # Is the below approach convoluted? yes - # Ok but is it inefficient? probably - # Ok but at least I don't have to repeat the check at every rule (I'm clinically insane) - _ruleGetter = lambda reaction : reaction.gene_reaction_rule - ruleExtractor = (lambda reaction : - rulesUtils.parseRuleToNestedList(_ruleGetter(reaction))) if asParsed else _ruleGetter - - return { - reaction.id : ruleExtractor(reaction) - for reaction in model.reactions - if reaction.gene_reaction_rule } - -def generate_reactions(model :cobra.Model, *, asParsed = True) -> Dict[ReactionId, str]: - """ - Generates a dictionary mapping reaction ids to reaction formulas from the model. - - Args: - model : the model to derive data from. - asParsed : if True parses the reactions to an optimized runtime format, otherwise leaves them as they are. - - Returns: - Dict[ReactionId, str] : the generated dictionary. - """ - - unparsedReactions = { - reaction.id : reaction.reaction - for reaction in model.reactions - if reaction.reaction - } - - if not asParsed: return unparsedReactions - - return reactionUtils.create_reaction_dict(unparsedReactions) - -def get_medium(model:cobra.Model) -> pd.DataFrame: - trueMedium=[] - for r in model.reactions: - positiveCoeff=0 - for m in r.metabolites: - if r.get_coefficient(m.id)>0: - positiveCoeff=1; - if (positiveCoeff==0 and r.lower_bound<0): - trueMedium.append(r.id) - - df_medium = pd.DataFrame() - df_medium["reaction"] = trueMedium - return df_medium - -def generate_bounds(model:cobra.Model) -> pd.DataFrame: - - rxns = [] - for reaction in model.reactions: - rxns.append(reaction.id) - - bounds = pd.DataFrame(columns = ["lower_bound", "upper_bound"], index=rxns) - - for reaction in model.reactions: - bounds.loc[reaction.id] = [reaction.lower_bound, reaction.upper_bound] - return bounds - - -###############################- FILE SAVING -################################ -def save_as_csv_filePath(data :dict, file_path :utils.FilePath, fieldNames :Tuple[str, str]) -> None: - """ - Saves any dictionary-shaped data in a .csv file created at the given file_path as FilePath. - - Args: - data : the data to be written to the file. - file_path : the path to the .csv file. - fieldNames : the names of the fields (columns) in the .csv file. - - Returns: - None - """ - with open(file_path.show(), 'w', newline='') as csvfile: - writer = csv.DictWriter(csvfile, fieldnames = fieldNames, dialect="excel-tab") - writer.writeheader() - - for key, value in data.items(): - writer.writerow({ fieldNames[0] : key, fieldNames[1] : value }) - -def save_as_csv(data :dict, file_path :str, fieldNames :Tuple[str, str]) -> None: - """ - Saves any dictionary-shaped data in a .csv file created at the given file_path as string. - - Args: - data : the data to be written to the file. - file_path : the path to the .csv file. - fieldNames : the names of the fields (columns) in the .csv file. - - Returns: - None - """ - with open(file_path, 'w', newline='') as csvfile: - writer = csv.DictWriter(csvfile, fieldnames = fieldNames, dialect="excel-tab") - writer.writeheader() - - for key, value in data.items(): - writer.writerow({ fieldNames[0] : key, fieldNames[1] : value }) - -###############################- ENTRY POINT -################################ -def main() -> None: - """ - Initializes everything and sets the program in motion based on the fronted input arguments. - - Returns: - None - """ - # get args from frontend (related xml) - global ARGS - ARGS = process_args() - - # this is the worst thing I've seen so far, congrats to the former MaREA devs for suggesting this! - if os.path.isdir(ARGS.out_dir) == False: os.makedirs(ARGS.out_dir) - - # load custom model - model = load_custom_model( - utils.FilePath.fromStrPath(ARGS.input), utils.FilePath.fromStrPath(ARGS.name).ext) - - # generate data - rules = generate_rules(model, asParsed = False) - reactions = generate_reactions(model, asParsed = False) - bounds = generate_bounds(model) - medium = get_medium(model) - - # save files out of collection: path coming from xml - save_as_csv(rules, ARGS.out_rules, ("ReactionID", "Rule")) - save_as_csv(reactions, ARGS.out_reactions, ("ReactionID", "Reaction")) - bounds.to_csv(ARGS.out_bounds, sep = '\t') - medium.to_csv(ARGS.out_medium, sep = '\t') - -if __name__ == '__main__': - main() \ No newline at end of file diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/utils/general_utils.py --- a/marea_2/utils/general_utils.py Thu Sep 19 10:00:47 2024 +0000 +++ b/marea_2/utils/general_utils.py Wed Nov 06 18:02:22 2024 +0000 @@ -10,7 +10,6 @@ from typing import Any, Callable, Dict, Generic, List, Optional, TypeVar, Union import pandas as pd -import cobra # FILES class FileFormat(Enum): @@ -516,9 +515,7 @@ Recon = "Recon" ENGRO2 = "ENGRO2" - ENGRO2_no_legend = "ENGRO2_no_legend" HMRcore = "HMRcore" - HMRcore_no_legend = "HMRcore_no_legend" Custom = "Custom" # Exists as a valid variant in the UI, but doesn't point to valid file paths. def __raiseMissingPathErr(self, path :Optional[FilePath]) -> None: @@ -550,24 +547,5 @@ path = customPath if self is Model.Custom else FilePath(f"{self.name}_map", FileFormat.SVG, prefix = f"{toolDir}/local/svg metabolic maps/") self.__raiseMissingPathErr(path) return readSvg(path, customErr = DataErr(path, f"custom map in wrong format")) - - def getCOBRAmodel(self, toolDir = ".", customPath :Optional[FilePath] = None, customExtension :Optional[FilePath]=None)->cobra.Model: - if(self is Model.Custom): - return self.load_custom_model(customPath, customExtension) - else: - return cobra.io.read_sbml_model(FilePath(f"{self.name}", FileFormat.XML, prefix = f"{toolDir}/local/models/").show()) - - def load_custom_model(self, file_path :FilePath, ext :Optional[FileFormat] = None) -> cobra.Model: - ext = ext if ext else file_path.ext - try: - if ext is FileFormat.XML: - return cobra.io.read_sbml_model(file_path.show()) - - if ext is FileFormat.JSON: - return cobra.io.load_json_model(file_path.show()) - - except Exception as e: raise DataErr(file_path, e.__str__()) - raise DataErr(file_path, - f"Fomat \"{file_path.ext}\" is not recognized, only JSON and XML files are supported.") def __str__(self) -> str: return self.value \ No newline at end of file diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/utils/reaction_parsing.py diff -r 60e96b950829 -r 9cb6eaa3c2b8 marea_2/utils/rule_parsing.py