Python Model._addSexSpecificity方法代码示例

# 需要导入模块: from dipper.models.Model import Model [as 别名]
# 或者: from dipper.models.Model.Model import _addSexSpecificity [as 别名]

#.........这里部分代码省略.........
                # Make the sex-qualified genotype,
                # which is what the phenotype is associated with
                sex_qualified_genotype_id = \
                    self.make_id((
                        colony_id + phenotyping_center + zygosity +
                        strain_accession_id + sex))
                sex_qualified_genotype_label = genotype_name + ' (' + sex + ')'

                sq_type_id = self.resolve(sex, False)

                if sq_type_id == sex:
                    sq_type_id = self.globaltt['intrinsic_genotype']
                    LOG.warning(
                        "Unknown sex qualifier %s, adding as intrinsic_genotype",
                        sex)

                geno.addGenotype(
                    sex_qualified_genotype_id, sex_qualified_genotype_label, sq_type_id)
                geno.addParts(
                    genotype_id, sex_qualified_genotype_id,
                    self.globaltt['has_variant_part'])

                if genomic_background_id is not None and genomic_background_id != '':
                    # Add the taxon to the genomic_background_id
                    geno.addTaxon(taxon_id, genomic_background_id)
                else:
                    # add it as the genomic background
                    geno.addTaxon(taxon_id, genotype_id)

                # #############    BUILD THE G2P ASSOC    #############
                # from an old email dated July 23 2014:
                # Phenotypes associations are made to
                # imits colony_id+center+zygosity+gender

                phenotype_id = mp_term_id

                # it seems that sometimes phenotype ids are missing.
                # indicate here
                if phenotype_id is None or phenotype_id == '':
                    LOG.warning(
                        "No phenotype id specified for row %d: %s",
                        line_counter, str(row))
                    continue
                # hard coded ECO code
                eco_id = self.globaltt['mutant phenotype evidence']

                # the association comes as a result of a g2p from
                # a procedure in a pipeline at a center and parameter tested

                assoc = G2PAssoc(
                    graph, self.name, sex_qualified_genotype_id, phenotype_id)
                assoc.add_evidence(eco_id)
                # assoc.set_score(float(p_value))

                # TODO add evidence instance using
                # pipeline_stable_id +
                # procedure_stable_id +
                # parameter_stable_id

                assoc.add_association_to_graph()
                assoc_id = assoc.get_association_id()

                model._addSexSpecificity(assoc_id, self.resolve(sex))

                # add a free-text description
                try:
                    description = ' '.join((
                        mp_term_name, 'phenotype determined by', phenotyping_center,
                        'in an', procedure_name, 'assay where', parameter_name.strip(),
                        'was measured with an effect_size of',
                        str(round(float(effect_size), 5)),
                        '(p =', "{:.4e}".format(float(p_value)), ').'))
                except ValueError:
                    description = ' '.join((
                        mp_term_name, 'phenotype determined by', phenotyping_center,
                        'in an', procedure_name, 'assay where', parameter_name.strip(),
                        'was measured with an effect_size of', str(effect_size),
                        '(p =', "{0}".format(p_value), ').'))

                study_bnode = self._add_study_provenance(
                    phenotyping_center, colony_raw, project_fullname, pipeline_name,
                    pipeline_stable_id, procedure_stable_id, procedure_name,
                    parameter_stable_id, parameter_name, statistical_method,
                    resource_name, line_counter)

                evidence_line_bnode = self._add_evidence(
                    assoc_id, eco_id, p_value, percentage_change, effect_size,
                    study_bnode)

                self._add_assertion_provenance(assoc_id, evidence_line_bnode)

                model.addDescription(evidence_line_bnode, description)

                # resource_id = resource_name
                # assoc.addSource(graph, assoc_id, resource_id)

                if not self.test_mode and limit is not None and line_counter > limit:
                    break

        return

# 需要导入模块: from dipper.models.Model import Model [as 别名]
# 或者: from dipper.models.Model.Model import _addSexSpecificity [as 别名]
    def _add_g2p_assoc(self, graph, strain_id, sex, assay_id, phenotypes, comment):
        """
        Create an association between a sex-specific strain id
        and each of the phenotypes.
        Here, we create a genotype from the strain,
        and a sex-specific genotype.
        Each of those genotypes are created as anonymous nodes.

        The evidence code is hardcoded to be:
            ECO:experimental_phenotypic_evidence.

        :param g:
        :param strain_id:
        :param sex:
        :param assay_id:
        :param phenotypes: a list of phenotypes to association with the strain
        :param comment:
        :return:

        """
        geno = Genotype(graph)
        model = Model(graph)
        eco_id = self.globaltt['experimental phenotypic evidence']
        strain_label = self.idlabel_hash.get(strain_id)
        # strain genotype
        genotype_id = '_:'+'-'.join((re.sub(r':', '', strain_id), 'genotype'))
        genotype_label = '[' + strain_label + ']'

        sex_specific_genotype_id = '_:'+'-'.join((
            re.sub(r':', '', strain_id), sex, 'genotype'))
        if strain_label is not None:
            sex_specific_genotype_label = strain_label + ' (' + sex + ')'
        else:
            sex_specific_genotype_label = strain_id + '(' + sex + ')'

        genotype_type = self.globaltt['sex_qualified_genotype']
        if sex == 'm':
            genotype_type = self.globaltt['male_genotype']
        elif sex == 'f':
            genotype_type = self.globaltt['female_genotype']

        # add the genotype to strain connection
        geno.addGenotype(
            genotype_id, genotype_label,
            self.globaltt['genomic_background'])
        graph.addTriple(
            strain_id, self.globaltt['has_genotype'], genotype_id)

        geno.addGenotype(
            sex_specific_genotype_id, sex_specific_genotype_label,
            genotype_type)

        # add the strain as the background for the genotype
        graph.addTriple(
            sex_specific_genotype_id,
            self.globaltt['has_sex_agnostic_part'],
            genotype_id)

        # #############    BUILD THE G2P ASSOC    #############
        # TODO add more provenance info when that model is completed

        if phenotypes is not None:
            for phenotype_id in phenotypes:
                assoc = G2PAssoc(
                    graph, self.name, sex_specific_genotype_id, phenotype_id)
                assoc.add_evidence(assay_id)
                assoc.add_evidence(eco_id)
                assoc.add_association_to_graph()
                assoc_id = assoc.get_association_id()
                model.addComment(assoc_id, comment)
                model._addSexSpecificity(assoc_id, self.resolve(sex))

        return