class Metabolite(BiologicalModel):
name = dmodels.CharField(max_length=512,
di_display_name='metabolite_name',
di_show=True)
derivative_group = dmodels.ForeignKey('DerivativeGroup',
null=True,
blank=True)
co_a_derivative = dmodels.ForeignKey('CoADerivative',
null=True,
blank=True)
def __str__(self):
return self.name
class GCMSData(ExperimentalData):
derivative_group = dmodels.ForeignKey('DerivativeGroup',
on_delete=models.CASCADE)
class Meta:
unique_together = (('derivative_group', 'experiment'), )
verbose_name_plural = 'Metabolome GCMS data'
def __str__(self):
return 'Metabolome GCMS datapoint'
class CoAData(ExperimentalData):
co_a_derivative = dmodels.ForeignKey('CoADerivative',
on_delete=models.PROTECT)
stderr = dmodels.FloatField(null=True, blank=True, di_show=True)
class Meta:
unique_together = (('co_a_derivative', 'experiment'), )
verbose_name_plural = 'CoA data'
def __str__(self):
return 'CoA datapoint'
class ProteomeData(MeasurementModel):
locus = dmodels.ForeignKey('Locus', on_delete=models.PROTECT)
fold_change = dmodels.FloatField(di_show=True)
adjusted_p_value = dmodels.FloatField(di_show=True,
validators=[validate_probabilty])
unique_peptides = dmodels.IntegerField()
class Meta:
unique_together = (('locus', 'experiment'), )
verbose_name_plural = 'Proteom data'
def __str__(self):
return 'Proteome Datapoint'
class TranscriptomeData(MeasurementModel):
locus = dmodels.ForeignKey('Locus', on_delete=models.PROTECT)
class Meta:
abstract = True
unique_together = (('locus', 'experiment'), )
def __str__(self):
try:
return '{}: {:10.2f}'.format(self.transcript.transcript_identifier,
self.mean_rpkm)
except:
return '{}'.format(self.mean_rpkm)
class FluxData(MeasurementModel):
flux = dmodels.FloatField(di_show=True, validators=[validate_flux])
flux_min = dmodels.FloatField(di_show=True,
di_display_name='lb',
validators=[validate_flux])
flux_max = dmodels.FloatField(di_show=True,
di_display_name='ub',
validators=[validate_flux])
reaction = dmodels.ForeignKey('Reaction', on_delete=models.CASCADE)
class Meta:
unique_together = ((
'reaction',
'experiment',
))
verbose_name_plural = 'Fluxes'
def __str__(self):
return 'Flux datapoint'
class Experiment(models.Model, DisbiExperiment):
EXPERIMENT_TYPE_CHOICES = (
('transcriptome', 'Transcriptome'),
('proteome', 'Proteome'),
('metabolome', 'Metabolome'),
('flux', 'Predicted Flux'),
)
experiment_type = dmodels.CharField(max_length=45,
choices=EXPERIMENT_TYPE_CHOICES,
di_choose=True)
# The first name is the DB name, the second is human readable.
EXPERIMENT_METHOD_CHOICES = (
('Transcriptome', (('rnaseq', 'RNAseq'), )),
('Proteome', (('shotgun', 'shotgun'), )),
('Metabolome', (
('gcms', 'GCMS'),
('coa', 'CoA-method'),
)),
('Predicted Flux', (('fba', 'FBA'), )),
)
experiment_method = dmodels.CharField(max_length=45,
choices=EXPERIMENT_METHOD_CHOICES,
di_choose=True)
c_source = dmodels.CharField(max_length=45,
blank=True,
verbose_name='Carbon source',
di_choose=True,
di_show=True,
di_combinable=True)
place = dmodels.CharField(max_length=45)
group = dmodels.CharField(max_length=45)
raw_data = dmodels.ForeignKey(
'RawData', help_text='A file with the raw data for the experiment')
notes = dmodels.TextField(blank=True, default='')
class Meta:
unique_together = (('experiment_type', 'experiment_method', 'c_source',
'group', 'raw_data'), )
def __str__(self):
return '{}. {}: {}'.format(
self.id,
self.get_experiment_type_display(),
self.get_experiment_method_display(),
)
def clean(self):
"""
Check whether the experiment method matches the experiment type.
"""
opt_groups = get_optgroups(self.EXPERIMENT_METHOD_CHOICES)
hr_experiment_type = get_hr_val(self.EXPERIMENT_TYPE_CHOICES,
self.experiment_type)
if self.experiment_method not in opt_groups[hr_experiment_type]:
hr_experiment_method = get_hr_val(
remove_optgroups(self.EXPERIMENT_METHOD_CHOICES),
self.experiment_method)
raise ValidationError(
_('{type} does not belong to the method {method}.'.format(
type=hr_experiment_type, method=hr_experiment_method)))
def c_source_display(self):
return self.c_source if self.c_source else '-'
c_source_display.short_description = 'Carbon source'
class MeasurementModel(models.Model):
"""Base class for clustering the measurement models."""
experiment = dmodels.ForeignKey('Experiment', on_delete=models.CASCADE)
class Meta:
abstract = True