m2m’s API

Workflow

m2m workflow

metage2metabo.m2m.m2m_workflow.add_targets_to_instance(instancefile, output_dir, target_set)

Add targets to the ASP community instance file.

Parameters:

• instancefile (str) – instance filepath

• output_dir (str) – directory for results

• target_set (set) – targets to be added

Returns:

new instance filepath

Return type:

str

metage2metabo.m2m.m2m_workflow.metacom_analysis(sbml_dir, out_dir, seeds, host_mn, targets_file, cpu_number=1, target_com_scope=None)

Run the metabolism community analysis part of m2m.

Parameters:

• sbml_dir (str) – sbml input directory

• out_dir (str) – results directory

• seeds (str) – seeds file

• host_mn (str) – metabolic network file for host

• targets_file (str) – targets file

• cpu_number (int) – number of CPU to use for multiprocessing

• target_com_scope (bool) – if True, will use all metabolties in com_scope as targets for minimal community predictions.

metage2metabo.m2m.m2m_workflow.run_workflow(inp_dir, out_dir, nb_cpu, clean, seeds, noorphan_bool, padmet_bool, host_mn, targets_file, use_pwt_xml, target_com_scope=None, standalone=None)

Run the whole m2m workflow.

Parameters:

• inp_dir (str) – genomes directory

• out_dir (str) – results directory

• nb_cpu (int) – cpu number for multi-processing

• clean (bool) – clean PGDB and re-run them

• seeds (str) – seeds file

• noorphan_bool (bool) – ignores orphan reactions if True

• padmet_bool (bool) – creates padmet files if True

• host_mn (str) – metabolic network file for host

• targets_file (str) – targets file

• use_pwt_xml (bool) – use Pathway Tools XML instead of creating them with padmet

• target_com_scope (bool) – if True, will use all metabolties in com_scope as targets for minimal community predictions.

• standalone (bool) – use standalone mode of Pathway Tools

metage2metabo.m2m.m2m_workflow.targets_producibility(m2m_out_dir, union_targets_iscope, targets_cscope, addedvalue_targets, user_targets=None, target_com_scope=None)

Create a json summarizing the producibility of the targets (either the addedvalue or the user provided targets)

Parameters:

• m2m_out_dir (str) – M2M results directory

• union_targets_iscope (list) – targets producible by indiviual

• targets_cscope (list) – targets producible by community

• addedvalue_targets (list) – targets produbed by the community and not by individual

• user_targets (list) – targets provided by the user

• target_com_scope (bool) – if True, will use all metabolties in com_scope as targets for minimal community predictions.

Reconstruction

metage2metabo.m2m.reconstruction.analyze_recon(sbml_folder, output_stat_file, padmet_folder=None, padmet_bool=None, nb_cpu=1)

Analyze the sbml and/or the padmet files after metabolic network reconstruction. And write the result in a file.

Parameters:

• sbml_folder (str) – directory of SBML files

• output_stat_file (str) – path to output stat file

• padmet_folder (str) – directory of PADMET files

• padmet_bool (bool) – use or not the padmet files

• nb_cpu (int) – number of CPU to use

metage2metabo.m2m.reconstruction.create_padmet_stat(species_name, padmet_file)

Extract reactions/pathways/compounds/genes from a padmet file.

Parameters:

• species_name (str) – species names

• padmet_file (str) – path to a padmet file

Returns

list: [species name, list of genes, list of reactions, list of reactions associated with genes, list of compounds, list of pathways]

metage2metabo.m2m.reconstruction.create_sbml_stat(species_name, sbml_file)

Extract reactions/pathways/compounds/genes from a sbml file.

Parameters:

• species_name (str) – species names

• sbml_file (str) – path to a sbml file

Returns

list: [species name, list of genes, list of reactions, list of reactions associated with genes, list of compounds]

metage2metabo.m2m.reconstruction.genomes_to_pgdb(genomes_dir, output_dir, cpu, clean, use_pwt_xml, standalone=None)

Run Pathway Tools on each genome of the repository

Parameters:

• genomes_dir (str) – genome repository

• output_dir (str) – output repository

• cpu (int) – number of CPUs to use

• clean (bool) – delete PGDBs in ptools-local coresponding to the input data

• use_pwt_xml (bool) – use Pathway Tools XML instead of creating them with padmet

• standalone (bool) – use standalone mode of Pathway Tools

Returns:

pgdb repository

Return type:

pgdb_dir (str)

metage2metabo.m2m.reconstruction.mean_sd_data(datas)

Compute the mean and standard deviation from a list.

Parameters:

datas (list) – list of integer/float

Returns

mean_data (float): mean of the list sd_data (flaot): standard deviation of the lsit

metage2metabo.m2m.reconstruction.recon(inp_dir, out_dir, noorphan_bool, padmet_bool, sbml_level, nb_cpu, clean, use_pwt_xml, standalone=None)

Run metabolic network reconstruction with Pathway Tools and get SBMLs.

Parameters:

• inp_dir (str) – genomes directory

• out_dir (str) – results directory

• noorphan_bool (bool) – ignores orphan reactions if True

• padmet_bool (bool) – creates padmet files if True

• sbml_level (str) – SBML level (2 or 3)

• nb_cpu (int) – number of CPU for multiprocessing

• clean (bool) – re-run metabolic reconstructions that are already available if found

• use_pwt_xml (bool) – use Pathway Tools XML instead of creating them with padmet

• standalone (bool) – use standalone mode of Pathway Tools

Returns:

PGDB directory (str), SBML directory (str)

Return type:

tuple

metage2metabo.m2m.reconstruction.update_pathway_tools_xml(input_sbml, output_sbml)

Update XML from Pathway Tools by adding a ‘M_’ prefix to avoid issue, when using metaboltie IDs.

Parameters:

• input_sbml (str) – path to xml input file

• output_sbml (str) – path to xml output file

Individual scope

metage2metabo.m2m.individual_scope.analyze_indiv_scope(scope_dict, seeds_status_dict, seeds)

Analyze the output of Menescope, stored in two dictionaries

Parameters:

• scope_dict (dict) – output of all menescope runs

• seeds_status_dict (dict) – production status of seeds in all menescope runs

• seeds (str) – SBML seeds file

Returns:

union of all the individual scopes

Return type:

set

metage2metabo.m2m.individual_scope.indiv_scope_on_species(sbml_path, bname, seeds_path)

Run Menetools and analyse individual metabolic capabilities on a sbml.

Parameters:

• sbml_path (str) – path to SBML file

• bname (str) – name linked to SBML file

• seeds_path (str) – path to SBML seeds file

Returns:

[boolean error, bname, dictionary containing menescope results]

Return type:

list

metage2metabo.m2m.individual_scope.indiv_scope_run(sbml_dir, seeds, output_dir, cpu_number=1)

Run Menetools and analyse individual metabolic capabilities.

Parameters:

• sbml_dir (str) – directory of SBML files

• seeds (str) – SBML seeds file

• output_dir (str) – directory for results

• cpu_number (int) – number of CPU to use for multiprocessing

Returns:

path to output file for scope from Menetools analysis

Return type:

str

metage2metabo.m2m.individual_scope.iscope(sbmldir, seeds, out_dir, cpu_number=1)

Compute individual scopes (reachable metabolites) for SBML files in a directory.

Parameters:

• sbmldir (str) – SBML files directory

• seeds (str) – SBML seeds file

• out_dir (str) – output directory

• cpu_number (int) – number of CPU to use for multiprocessing

Returns:

union of reachable metabolites for all metabolic networks

Return type:

set

metage2metabo.m2m.individual_scope.reverse_scope(scope_dict, output_dir)

Reverse a scope dictionary by focusing on metabolite producers.

Parameters:

• scope_dict (dict) – dict of scope

• output_dir (str) – path to output directory

Returns:

paths to the JSON and TSV outputs

Return type:

(str, str)

Community scope

metage2metabo.m2m.community_scope.comm_scope_run(instance, output_dir, host_mn=None)

Run Miscoto_scope and analyse community metabolic capabilities

Parameters:

• instance (str) – instance filepath

• output_dir (str) – directory for results

• host_mn (str) – metabolic network file for host

Returns:

microbiota scope dict: contribution of microbes to the scope

Return type:

set

metage2metabo.m2m.community_scope.cscope(sbmldir, seeds, out_dir, targets_file=None, host=None)

Run community scope.

Parameters:

• sbmldir (str) – SBML files directory

• seeds (str) – SBML file for seeds

• out_dir (str) – output directory

• targets_file (str) – targets file

• host (str, optional) – Defaults to None. Host metabolic network (SBML)

Returns:

instance file (str) and community scope (set)

Return type:

tuple

metage2metabo.m2m.community_scope.instance_community(sbml_dir, seeds, output_dir, targets_file=None, host_mn=None)

Create ASP instance for community analysis.

Parameters:

• sbml_dir (str) – directory of symbionts SBML files

• seeds (str) – seeds SBML file

• output_dir (str) – directory for results

• targets_file (str) – targets file

• host_mn (str) – metabolic network file for host

Returns:

instance filepath

Return type:

str

metage2metabo.m2m.community_scope.reverse_cscope(bact_contrib, reverse_dict, output_dir)

Reverse a scope dictionary by focusing on metabolite producers.

Parameters:

• bact_contrib (dict) – dict of bacteria contributions to community scope

• reverse_dict (dict) – dict of metabolite producers in community

• output_dir (str) – path to output directory

Returns:

paths to the JSON and TSV outputs

Return type:

(str, str)

Cooperation potential (added-value)

metage2metabo.m2m.community_addedvalue.addedvalue(iscope_rm, cscope_rm, out_dir)

Compute the added value of considering interaction with microbiota metabolism rather than individual metabolisms.

Parameters:

• iscope_rm (set) – union of metabolites in all individual scopes

• cscope_rm (set) – metabolites reachable by community/microbiota

• out_dir (str) – output directory

Returns:

set of metabolites that can only be reached by a community

Return type:

set

Minimal community

metage2metabo.m2m.minimal_community.compute_mincom(instancefile, miscoto_dir)

Run minimal community selection and analysis.

Parameters:

• instancefile (str) – filepath to instance file

• miscoto_dir (str) – directory with results

Returns:

results of miscoto_mincom analysis

Return type:

dict

metage2metabo.m2m.minimal_community.mincom(instance_w_targets, seeds, targets, out_dir)

Compute minimal community selection and show analyses.

Parameters:

• instance_w_targets (str) – ASP instance filepath

• seeds (str) – seeds filepath

• targets (str) – targets set

• out_dir (str) – results directory

SBML Management

metage2metabo.sbml_management.compare_seeds_and_targets(seedfile, targetfile)

Returns the intersection of the seeds and the targets

Parameters:

• seedfile (str) – path to seeds SBML file

• targetfile (str) – path to targets SBML file

Returns:

intersection of seeds and targets

Return type:

set

metage2metabo.sbml_management.create_species_sbml(metabolites, outputfile)

Create a SBML files with a list of species containing metabolites of the input set. Check if there are forbidden SBML characters in the metabolite IDs/ If yes, exit.

Parameters:

• metabolites (set) – set of metabolites

• outputfile (str) – SBML file to be written

metage2metabo.sbml_management.get_compounds(sbml_file)

Get compound from sbml

Parameters:

sbml_file (str) – SBML file

Returns:

compound

Return type:

list

metage2metabo.sbml_management.pgdb_to_sbml(pgdb_dir, output_dir, noorphan_bool, padmet_bool, sbml_level, cpu)

Turn Pathway Tools PGDBs into SBML2 files using Padmet

Parameters:

• pgdb_dir (str) – PGDB directory

• output_dir (str) – results directory

• noorphan_bool (bool) – ignores orphan reactions if True

• padmet_bool (bool) – creates padmet files if True

• sbml_level (int) – SBML level

• cpu (int) – number of CPU for multi-process

Returns:

SBML directory if successful

Return type:

sbml_dir (str)

metage2metabo.sbml_management.run_pgdb_to_sbml(species_multiprocess_data)

Turn PGDBs into SBML2 using multi-processing.

Parameters:

species_multiprocess_data (list) – pathname to species pgdb dir, pathname to species sbml file

Returns:

Check if sbml file exists

Return type:

sbml_check (bool)

Utils

metage2metabo.utils.check_absolute_path(directory, target)

Check if the extracted element is inside the output directory. If not, it is a potential path traversal attempt.

Parameters:

• directory (str) – path to output directory for extraction.

• target (str) – path of file contained in tar file.

metage2metabo.utils.check_program(program)

Check whether Pathway Tools is in the PATH

Returns:

True if Pathway Tools is in the PATH, False otherwise

Return type:

bool

metage2metabo.utils.file_or_folder(variable_folder_file)

Check if the variable is file or a folder

Parameters:

variable_folder_file (str) – path to a file or a folder

Returns:

{name of input file: path to input file}

Return type:

dict

metage2metabo.utils.get_basename(filepath)

Return the basename of given filepath.

Parameters:

filepath (str) – path to a file

Returns:

basename

Return type:

str

>>> basename('~/an/interesting/file.txt')
'file

metage2metabo.utils.get_extension(filepath)

Get the extension of a filepath

Parameters:

filepath (str) – path to a file

Returns:

extention of the file

Return type:

str

>>> extension('~/an/interesting/file.lp')
'lp'
>>> extension('nothing')
''
>>> extension('nothing.important')
'important'

metage2metabo.utils.is_valid_dir(dirpath)

Return True if directory exists or can be created (then create it)

Parameters:

dirpath (str) – path of directory

Returns:

True if dir exists, False otherwise

Return type:

bool

metage2metabo.utils.is_valid_file(filepath)

Return True if filepath exists

Parameters:

filepath (str) – path to file

Returns:

True if path exists, False otherwise

Return type:

bool

metage2metabo.utils.is_valid_path(filepath)

Return True if filepath is valid

Parameters:

filepath (str) – path to file

Returns:

True if path exists, False otherwise

Return type:

bool

metage2metabo.utils.safe_tar_extract_all(tar_file, outdir)

Perform a sanitized check to ensure no file outside the output folder will be modified.

Parameters:

• tar_file (str) – path to tar file.

• outdir (str) – path to output directory for extraction.

m2m_analysis

m2m_analysis workflow

Enumeration of Minimal communities

metage2metabo.m2m_analysis.enumeration.convert_groups_to_equation(bacterial_groups)

Convert bacterial groups (from extract_groups_from_enumeration) to boolean equation.

Parameters:

bacterial_groups (list) – list of frozenset containing each different group of the community

Returns:

string representing the boolean equation of minimal communities

Return type:

boolean_equation (str)

metage2metabo.m2m_analysis.enumeration.enumeration(sbml_folder, target_file, seed_file, output_json, host_file)

Run miscoto enumeration on one target file

Parameters:

• sbml_folder (str) – sbml directory

• target_file (str) – targets file

• seed_file (str) – seeds file

• output_json (str) – path to json output

• host_file (str) – metabolic network file for host

Returns:

path to output json

Return type:

str

metage2metabo.m2m_analysis.enumeration.enumeration_analysis(sbml_folder, target_folder_file, seed_file, output_dir, host_file=None)

Run miscoto enumeration on input data

Parameters:

• sbml_folder (str) – sbml directory

• target_folder_file (str) – targets file or folder containing multiple sbmls

• seed_file (str) – seeds file

• output_dir (str) – results directory

• host_file (str) – metabolic network file for host

Returns:

{target_filename_without_extension: json_output_path}

Return type:

dict

metage2metabo.m2m_analysis.enumeration.extract_groups_from_enumeration(results)

From the results of the enumeration computes the boolean eaqution of the minimal communities. It is a very simple method that will fail for enumeration with numerous and complex combinations.

Parameters:

results (dict) – results dictionary of miscoto for the enumeration.

Returns:

list of frozenset containing each different group of the community

Return type:

bacterial_groups (list)

Creation of graph solution

Compression of graph

taxonomy

Main

metage2metabo.__main__.create_metadata(dict_args, duration, metadata_json_file)

Create metadata from args and package versions.

Parameters:

• dict_args (dict) – dict of args given to argparse

• duration (int) – time of the run

• metadata_json_file (str) – pat hto metadata output file

metage2metabo.__main__.main()

Run programm.

metage2metabo.__main__.main_added_value(sbmldir, seeds, outdir, host)

Run addedvalue command.

Parameters:

• sbmldir (str) – SBML file directory

• seeds (str) – SBML file for seeds

• outdir (str) – results directory

• host (str) – SBML file for host

metage2metabo.__main__.main_cscope(*allargs)

Run cscope command.

metage2metabo.__main__.main_iscope(*allargs)

Run iscope command.

metage2metabo.__main__.main_metacom(*allargs)

Run main workflow.

metage2metabo.__main__.main_mincom(sbmldir, seedsfiles, outdir, targets, host)

Run mincom command.

Parameters:

• sbmldir (str) – SBML files directory

• seedsfiles (str) – SBML file for seeds

• outdir (str) – results directory

• targets (str) – targets SBML file

• host (str) – SBML file for host

metage2metabo.__main__.main_recon(*allargs)

Run recon command.

metage2metabo.__main__.main_seeds(metabolites_file, outdir)

Run seeds command.

Parameters:

• metabolites_file (str) – text file with metabolites IDs, one per line

• outdir (str) – Results directory

metage2metabo.__main__.main_test(outdir, cpu)

Run test command.

Parameters:

• outdir (str) – directory containing the test data and the test output

• cpu (int) – number of cpu to use (recommended: 2)

metage2metabo.__main__.main_workflow(*allargs)

Run main workflow.