Light Sensitivity Experiment:¶
Reporting a repeated treatment design with ISA create mode¶
This example creates ISA study descriptor for study with sequential treatments organized in an arm. This shows how to use objects from the isatools.create component in a granular fashion. It creates each Element of the Study Arm at a time.
Finally, the study design plan is shown by serializing the ISA Study Design Model content as an ISA_design JSON document, which can be rendered in various ways (tables, figures).
Study metadata¶
# If executing the notebooks on `Google Colab`,uncomment the following command
# and run it to install the required python libraries. Also, make the test datasets available.
# !pip install -r requirements.txt
import os
import datetime
import json
from collections import OrderedDict
from isatools.model import (
Investigation,
Study,
Sample,
OntologyAnnotation,
StudyFactor,
FactorValue,
Characteristic,
Source,
Protocol,
Process
)
from isatools.create.model import (
Treatment,
NonTreatment,
StudyDesign,
StudyCell,
StudyArm,
ProductNode,
SampleAndAssayPlan,
AssayGraph
)
from isatools.create.constants import (
BASE_FACTORS,
SCREEN,
RUN_IN,
WASHOUT,
FOLLOW_UP,
SAMPLE,
EXTRACT,
LABELED_EXTRACT,
DATA_FILE
)
from isatools.isatab import dumps
from isatools.isajson import ISAJSONEncoder
investigation = Investigation()
investigation1 = Investigation() # to be used with the study create function
study = Study(filename="s_study_xover.txt")
study.identifier = "elifesprint2019-1"
study.title = "elifesprint2019-1: light sensitivity"
study.description = "a study about light sensitivity difference between a control population (n=10) and a genotype A population (n=10)."
study.submission_date = str(datetime.datetime.today())
study.public_release_date = str(datetime.datetime.today())
study.sources = [Source(name="source1")]
study.samples = [Sample(name="sample1")]
study.protocols = [Protocol(name="sample collection")]
study.process_sequence = [Process(executes_protocol=study.protocols[-1], inputs=[study.sources[-1]], outputs=[study.samples[-1]])]
investigation.studies = [study]
# Let's see the object :
investigation
isatools.model.Investigation(identifier='', filename='', title='', submission_date='', public_release_date='', ontology_source_references=[], publications=[], contacts=[], studies=[isatools.model.Study(filename='s_study_xover.txt', identifier='elifesprint2019-1', title='elifesprint2019-1: light sensitivity', description='a study about light sensitivity difference between a control population (n=10) and a genotype A population (n=10).', submission_date='2021-07-21 17:43:54.131318', public_release_date='2021-07-21 17:43:54.131358', contacts=[], design_descriptors=[], publications=[], factors=[], protocols=[isatools.model.Protocol(name='sample collection', protocol_type=isatools.model.OntologyAnnotation(term='', term_source=None, term_accession='', comments=[]), uri='', version='', parameters=[], components=[], comments=[])], assays=[], sources=[isatools.model.Source(name='source1', characteristics=[], comments=[])], samples=[isatools.model.Sample(name='sample1', characteristics=[], factor_values=[], derives_from=[], comments=[])], process_sequence=[isatools.model.Process(id="". name="None", executes_protocol=Protocol(
name=sample collection
protocol_type=
uri=
version=
parameters=0 ProtocolParameter objects
components=0 OntologyAnnotation objects
comments=0 Comment objects
), date="None", performer="None", inputs=[isatools.model.Source(name='source1', characteristics=[], comments=[])], outputs=[isatools.model.Sample(name='sample1', characteristics=[], factor_values=[], derives_from=[], comments=[])])], other_material=[], characteristic_categories=[], comments=[], units=[])], comments=[])
# print(dumps(investigation))
# print(json.dumps(investigation, cls=ISAJSONEncoder, sort_keys=True, indent=4, separators=(',', ': ')))
1. Creation of the first ISA Study Design Element and setting both element_type AND duration_unit attributes¶
# IMPORTANT: note how duration_unit value is supplied as an OntologyAnnotation object
nte1 = NonTreatment(element_type='screen', duration_unit=OntologyAnnotation(term="days"))
print(nte1)
NonTreatment(
type='screen',
duration=isatools.model.FactorValue(factor_name=isatools.model.StudyFactor(name='DURATION', factor_type=isatools.model.OntologyAnnotation(term='time', term_source=None, term_accession='', comments=[]), comments=[]), value=0.0, unit=isatools.model.OntologyAnnotation(term='days', term_source=None, term_accession='', comments=[]))
)
2. Creation of another ISA Study Design Element, of type Treatment¶
te1 = Treatment()
te1.type='radiological intervention'
print(te1)
"Treatment
(type=radiological intervention,
factor_values=[])
2.1 defining the first treatment as a vector of ISA factor values:¶
Under âISA Study Design Create modeâ, a Study Design Element of type Treatment needs to be defined by a vector of Factors and their respective associated Factor Values. This is done as follows:
f1 = StudyFactor(name='light', factor_type=OntologyAnnotation(term="electromagnetic energy"))
f1v = FactorValue(factor_name=f1, value="visible light at 3000K produced by LED array")
f2 = StudyFactor(name='dose', factor_type=OntologyAnnotation(term="quantity"))
# IMPORTANT: note how *FactorValue value* is supplied as an *numeral*
f2v = FactorValue(factor_name=f2, value=250, unit=OntologyAnnotation(term='lux'))
f3 = StudyFactor(name='duration', factor_type=OntologyAnnotation(term="time"))
f3v = FactorValue(factor_name=f3, value=1, unit=OntologyAnnotation(term='hr'))
print(f1v,f2v)
FactorValue(
factor_name=light
value='visible light at 3000K produced by LED array'
unit=
) FactorValue(
factor_name=dose
value=250
unit=lux
)
#assigning the factor values declared above to the ISA treatment element
te1.factor_values = [f1v,f2v,f3v]
print(te1)
"Treatment
(type=radiological intervention,
factor_values=[isatools.model.FactorValue(factor_name=isatools.model.StudyFactor(name='dose', factor_type=isatools.model.OntologyAnnotation(term='quantity', term_source=None, term_accession='', comments=[]), comments=[]), value=250, unit=isatools.model.OntologyAnnotation(term='lux', term_source=None, term_accession='', comments=[])), isatools.model.FactorValue(factor_name=isatools.model.StudyFactor(name='duration', factor_type=isatools.model.OntologyAnnotation(term='time', term_source=None, term_accession='', comments=[]), comments=[]), value=1, unit=isatools.model.OntologyAnnotation(term='hr', term_source=None, term_accession='', comments=[])), isatools.model.FactorValue(factor_name=isatools.model.StudyFactor(name='light', factor_type=isatools.model.OntologyAnnotation(term='electromagnetic energy', term_source=None, term_accession='', comments=[]), comments=[]), value='visible light at 3000K produced by LED array', unit=None)])
3. Creation of a second ISA Study Design Element, of type Treatment, following the same pattern.¶
te3 = Treatment()
te3.type = 'radiological intervention'
rays = StudyFactor(name='light', factor_type=OntologyAnnotation(term="electromagnetic energy"))
raysv = FactorValue(factor_name=rays, value='visible light at 3000K produced by LED array')
rays_intensity = StudyFactor(name='dose', factor_type=OntologyAnnotation(term="quantity"))
rays_intensityv= FactorValue(factor_name=rays_intensity, value = 250, unit=OntologyAnnotation(term='lux'))
rays_duration = StudyFactor(name = 'duration', factor_type=OntologyAnnotation(term="time"))
rays_durationv = FactorValue(factor_name=rays_duration, value=1, unit=OntologyAnnotation(term='hour'))
te3.factor_values = [raysv,rays_intensityv,rays_durationv]
print(te3)
"Treatment
(type=radiological intervention,
factor_values=[isatools.model.FactorValue(factor_name=isatools.model.StudyFactor(name='dose', factor_type=isatools.model.OntologyAnnotation(term='quantity', term_source=None, term_accession='', comments=[]), comments=[]), value=250, unit=isatools.model.OntologyAnnotation(term='lux', term_source=None, term_accession='', comments=[])), isatools.model.FactorValue(factor_name=isatools.model.StudyFactor(name='duration', factor_type=isatools.model.OntologyAnnotation(term='time', term_source=None, term_accession='', comments=[]), comments=[]), value=1, unit=isatools.model.OntologyAnnotation(term='hour', term_source=None, term_accession='', comments=[])), isatools.model.FactorValue(factor_name=isatools.model.StudyFactor(name='light', factor_type=isatools.model.OntologyAnnotation(term='electromagnetic energy', term_source=None, term_accession='', comments=[]), comments=[]), value='visible light at 3000K produced by LED array', unit=None)])
4. Creation of âwash outâ period as an ISA Study Design Element.¶
# Creation of another ISA element, which is not a Treatment element, which is of type `screen` by default
# nte2 = NonTreatment()
# nte2.type = 'washout'
# net2.duration_unit=OntologyAnnotation(term="days")
nte2 = NonTreatment(element_type='washout', duration_unit=OntologyAnnotation(term="days"))
print(nte2)
NonTreatment(
type='washout',
duration=isatools.model.FactorValue(factor_name=isatools.model.StudyFactor(name='DURATION', factor_type=isatools.model.OntologyAnnotation(term='time', term_source=None, term_accession='', comments=[]), comments=[]), value=0.0, unit=isatools.model.OntologyAnnotation(term='days', term_source=None, term_accession='', comments=[]))
)
# setting the factor values associated with 'default' DURATION Factor associated with such elements
nte2.duration.value=2
nte2.duration.unit=OntologyAnnotation(term="weeks")
5. Creation of âfollow-upâ period as an ISA Study Design Element.¶
nte3 = NonTreatment(element_type='follow-up', duration_value=1, duration_unit=OntologyAnnotation(term="month"))
#print(nte3)
6. Creation of the associated container, known as an ISA Cell for each ISA Element.¶
In this example, a single Element is hosted by a Cell, which must be named. In more complex designs (e.g. study designs with assymetric arms), a Cell may contain more than one Element, hence the list attribute.
st_cl1= StudyCell(name="st_cl1", elements=[nte1])
st_cl2= StudyCell(name="st_cl2", elements=[te1])
st_cl3= StudyCell(name="st_cl3", elements=[nte2])
st_cl4= StudyCell(name="st_cl4", elements=[te3])
st_cl5= StudyCell(name="st_cl5", elements=[nte3])
7. Creation of an ISA Study Arm and setting the number of subjects associated to that unique sequence of ISA Cells.¶
genotype_cat = OntologyAnnotation(term="genotype")
genotype_value1 = OntologyAnnotation(term="control - normal")
genotype_value2 = OntologyAnnotation(term="mutant")
arm1 = StudyArm(
name='Arm 1',
group_size=2
)
arm1.source_type=Characteristic(
category=genotype_cat,
value=genotype_value1
)
print(arm1)
"StudyArm(
name=Arm 1,
source_type=Characteristic(
category=genotype
value=control - normal
unit=
comments=0 Comment objects
),
group_size=2,
no. cells=0,
no. sample_assay_plans=0
)
8. Declaring an ISA Sample Assay Plan, defining which Sample are to be collected and which Assays to be used¶
whole_patient=ProductNode(
id_="MAT1",
name="subject",
node_type=SAMPLE,
size=1,
characteristics=[
Characteristic(
category=OntologyAnnotation(term='organism part'),
value=OntologyAnnotation(term='whole organism')
)
]
)
saliva=ProductNode(
id_="MAT2",
name="saliva",
node_type=SAMPLE,
size=1,
characteristics=[
Characteristic(
category=OntologyAnnotation(term='organism part'),
value=OntologyAnnotation(term='saliva')
)
]
)
Here we load an isa assay definition in the form of an ordered dictionary. It corresponds to an ISA configuration assay table but expressed in JSON.
We now show how to create an new AssayGraph structure from scratch, as if we were defining a completely new assay type.
light_sensitivity_phenotyping_1 = OrderedDict([
('measurement_type', OntologyAnnotation(term='melatonine concentration')),
('technology_type', OntologyAnnotation(term='radioimmunoprecipitation assay')),
('extraction', {}),
('extract', [
{
'node_type': EXTRACT,
'characteristics_category': OntologyAnnotation(term='extract type'),
'characteristics_value': OntologyAnnotation(term='extract'),
'size': 1,
'technical_replicates': None,
'is_input_to_next_protocols': True
}]),
('radioimmunoprecipitation', {
OntologyAnnotation(term='instrument'): [OntologyAnnotation(term='Beckon Dickison XYZ')],
OntologyAnnotation(term='antibody'): [OntologyAnnotation(term='AbCam antiMelatonine ')],
OntologyAnnotation(term='time point'): [OntologyAnnotation(term='1 hr'),
OntologyAnnotation(term='2 hr')]
}),
('raw_data_file', [
{
'node_type': DATA_FILE,
'size': 1,
'technical_replicates': 1,
'is_input_to_next_protocols': False
}
])
])
light_sensitivity_phenotyping_2 = OrderedDict([
('measurement_type', OntologyAnnotation(term='light sensitivity')),
('technology_type', OntologyAnnotation(term='electroencephalography')),
('data_collection', {
OntologyAnnotation(term='instrument'): [OntologyAnnotation(term='Somnotouch')],
OntologyAnnotation(term='sampling_rate'): [OntologyAnnotation(term='200 Hz')],
OntologyAnnotation(term='time point'): [OntologyAnnotation(term='1 hr'),
OntologyAnnotation(term='2 hr')]
}),
('raw_data_file', [
{
'node_type': DATA_FILE,
'size': 1,
'technical_replicates': 1,
'is_input_to_next_protocols': False
}
])
])
light_sensitivity_phenotyping_3 = OrderedDict([
('measurement_type', OntologyAnnotation(term='light sensitivity phenotyping')),
('technology_type', OntologyAnnotation(term='direct measurement')),
('data_collection', {
OntologyAnnotation(term='variables'): [OntologyAnnotation(term='sleepiness'),
OntologyAnnotation(term='heart rate'),
OntologyAnnotation(term='pupilla size')],
OntologyAnnotation(term='time point'): [OntologyAnnotation(term='1 hr'),
OntologyAnnotation(term='2 hr')]
}),
('raw_data_file', [
{
'node_type': DATA_FILE,
'size': 1,
'technical_replicates': 1,
'is_input_to_next_protocols': False
}
])
])
alterness_assay_graph = AssayGraph.generate_assay_plan_from_dict(light_sensitivity_phenotyping_1)
melatonine_assay_graph = AssayGraph.generate_assay_plan_from_dict(light_sensitivity_phenotyping_2)
general_phenotyping_assay_graph = AssayGraph.generate_assay_plan_from_dict(light_sensitivity_phenotyping_3)
sap1 = SampleAndAssayPlan(name='sap1', sample_plan=[whole_patient,saliva],assay_plan=[alterness_assay_graph,melatonine_assay_graph,general_phenotyping_assay_graph])
sap1.add_element_to_map(sample_node=saliva, assay_graph=melatonine_assay_graph)
sap1.add_element_to_map(sample_node=whole_patient, assay_graph=alterness_assay_graph)
sap1.add_element_to_map(sample_node=whole_patient,assay_graph=general_phenotyping_assay_graph)
9. Declaration of an ISA assay and linking specimen type and data acquisition plan for this assay¶
sap1.sample_to_assay_map
{isatools.create.model.ProductNode(id=MAT2, type=sample, name=saliva, characteristics=[isatools.model.Characteristic(category=isatools.model.OntologyAnnotation(term='organism part', term_source=None, term_accession='', comments=[]), value=isatools.model.OntologyAnnotation(term='saliva', term_source=None, term_accession='', comments=[]), unit=None, comments=[])], size=1, extension=None): {isatools.create.model.AssayGraph(id=cce3713d-dfd3-4942-8d87-cb391156d756, measurement_type=OntologyAnnotation(
term=light sensitivity
term_source=
term_accession=
comments=0 Comment objects
), technology_type=OntologyAnnotation(
term=electroencephalography
term_source=
term_accession=
comments=0 Comment objects
), nodes={isatools.create.model.ProductNode(id=raw_data_file_000_001, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None), isatools.create.model.ProtocolNode(id=data_collection_001, name=assay0 - data_collection, protocol_type=OntologyAnnotation(
term=assay0 - data_collection
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='instrument', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='Somnotouch', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='sampling_rate', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='200 Hz', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='2 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProtocolNode(id=data_collection_000, name=assay0 - data_collection, protocol_type=OntologyAnnotation(
term=assay0 - data_collection
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='instrument', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='Somnotouch', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='sampling_rate', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='200 Hz', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='1 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProductNode(id=raw_data_file_000_000, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None)}, links=[('data_collection_000', 'raw_data_file_000_000'), ('data_collection_001', 'raw_data_file_000_001')], quality_control=None)},
isatools.create.model.ProductNode(id=MAT1, type=sample, name=subject, characteristics=[isatools.model.Characteristic(category=isatools.model.OntologyAnnotation(term='organism part', term_source=None, term_accession='', comments=[]), value=isatools.model.OntologyAnnotation(term='whole organism', term_source=None, term_accession='', comments=[]), unit=None, comments=[])], size=1, extension=None): {isatools.create.model.AssayGraph(id=05599bfb-d02b-471e-b9b1-6ce6758791db, measurement_type=OntologyAnnotation(
term=melatonine concentration
term_source=
term_accession=
comments=0 Comment objects
), technology_type=OntologyAnnotation(
term=radioimmunoprecipitation assay
term_source=
term_accession=
comments=0 Comment objects
), nodes={isatools.create.model.ProductNode(id=extract_000_000, type=extract, name=extract, characteristics=[isatools.model.Characteristic(category=isatools.model.OntologyAnnotation(term='extract type', term_source=None, term_accession='', comments=[]), value=isatools.model.OntologyAnnotation(term='extract', term_source=None, term_accession='', comments=[]), unit=None, comments=[])], size=1, extension=None), isatools.create.model.ProtocolNode(id=extraction_000, name=assay0 - extraction, protocol_type=OntologyAnnotation(
term=assay0 - extraction
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[]), isatools.create.model.ProtocolNode(id=radioimmunoprecipitation_001_000, name=assay0 - radioimmunoprecipitation, protocol_type=OntologyAnnotation(
term=assay0 - radioimmunoprecipitation
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='instrument', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='Beckon Dickison XYZ', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='antibody', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='AbCam antiMelatonine ', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='2 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProductNode(id=raw_data_file_000_001, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None), isatools.create.model.ProtocolNode(id=radioimmunoprecipitation_000_000, name=assay0 - radioimmunoprecipitation, protocol_type=OntologyAnnotation(
term=assay0 - radioimmunoprecipitation
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='instrument', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='Beckon Dickison XYZ', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='antibody', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='AbCam antiMelatonine ', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='1 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProductNode(id=raw_data_file_000_000, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None)}, links=[('extract_000_000', 'radioimmunoprecipitation_000_000'), ('extract_000_000', 'radioimmunoprecipitation_001_000'), ('extraction_000', 'extract_000_000'), ('radioimmunoprecipitation_000_000', 'raw_data_file_000_000'), ('radioimmunoprecipitation_001_000', 'raw_data_file_000_001')], quality_control=None),
isatools.create.model.AssayGraph(id=d7726069-1823-4f49-b10c-8856036ad082, measurement_type=OntologyAnnotation(
term=light sensitivity phenotyping
term_source=
term_accession=
comments=0 Comment objects
), technology_type=OntologyAnnotation(
term=direct measurement
term_source=
term_accession=
comments=0 Comment objects
), nodes={isatools.create.model.ProductNode(id=raw_data_file_000_002, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None), isatools.create.model.ProductNode(id=raw_data_file_000_003, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None), isatools.create.model.ProtocolNode(id=data_collection_004, name=assay0 - data_collection, protocol_type=OntologyAnnotation(
term=assay0 - data_collection
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='variables', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='pupilla size', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='1 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProductNode(id=raw_data_file_000_004, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None), isatools.create.model.ProtocolNode(id=data_collection_000, name=assay0 - data_collection, protocol_type=OntologyAnnotation(
term=assay0 - data_collection
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='variables', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='sleepiness', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='1 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProductNode(id=raw_data_file_000_001, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None), isatools.create.model.ProtocolNode(id=data_collection_002, name=assay0 - data_collection, protocol_type=OntologyAnnotation(
term=assay0 - data_collection
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='variables', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='heart rate', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='1 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProtocolNode(id=data_collection_005, name=assay0 - data_collection, protocol_type=OntologyAnnotation(
term=assay0 - data_collection
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='variables', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='pupilla size', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='2 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProtocolNode(id=data_collection_003, name=assay0 - data_collection, protocol_type=OntologyAnnotation(
term=assay0 - data_collection
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='variables', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='heart rate', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='2 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProductNode(id=raw_data_file_000_005, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None), isatools.create.model.ProtocolNode(id=data_collection_001, name=assay0 - data_collection, protocol_type=OntologyAnnotation(
term=assay0 - data_collection
term_source=
term_accession=
comments=0 Comment objects
), uri=, description=, version=, parameter_values=[isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='variables', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='sleepiness', term_source=None, term_accession='', comments=[]), unit=None, comments=[]), isatools.model.ParameterValue(category=isatools.model.ProtocolParameter(parameter_name=isatools.model.OntologyAnnotation(term='time point', term_source=None, term_accession='', comments=[]), comments=[]), value=isatools.model.OntologyAnnotation(term='2 hr', term_source=None, term_accession='', comments=[]), unit=None, comments=[])]), isatools.create.model.ProductNode(id=raw_data_file_000_000, type=data file, name=raw_data_file, characteristics=[], size=1, extension=None)}, links=[('data_collection_000', 'raw_data_file_000_000'), ('data_collection_001', 'raw_data_file_000_001'), ('data_collection_002', 'raw_data_file_000_002'), ('data_collection_003', 'raw_data_file_000_003'), ('data_collection_004', 'raw_data_file_000_004'), ('data_collection_005', 'raw_data_file_000_005')], quality_control=None)}}
10. Build an ISA Study Design Arm by adding the first set of ISA Cells and setting the Sample Assay Plan¶
arm1.add_item_to_arm_map(st_cl1, sap1)
# print(arm1)
11 Now expanding the Arm by adding a new Cell, which uses the same Sample Assay Plan as the one used in Cell #1.¶
Of course, the Sample Assay Plan for this new Cell could be different. It would have to be to built as shown before.
arm1.add_item_to_arm_map(st_cl2, sap1)
# Adding the last section of the Arm, with a cell which also uses the same sample assay plan.
arm1.add_item_to_arm_map(st_cl3, sap1)
arm1.add_item_to_arm_map(st_cl4, sap1)
arm1.add_item_to_arm_map(st_cl5, sap1)
12. Creation of additional ISA Study Arms and setting the number of subjects associated to that unique sequence of ISA Cells.¶
arm2 = StudyArm(name='Arm 2')
arm2.group_size=2
arm2.source_type=Characteristic(category=genotype_cat,
value=genotype_value2)
# st_cl6= StudyCell(name="st_cl6", elements=[nte1])
# st_cl7= StudyCell(name="st_cl7", elements=[te1])
# st_cl8= StudyCell(name="st_cl8", elements=[nte2])
# st_cl9= StudyCell(name="st_cl9", elements=[te3])
# st_cl10= StudyCell(name="st_cl10", elements=[nte3])
arm2.source_type.category
arm2.add_item_to_arm_map(st_cl1,sap1)
arm2.add_item_to_arm_map(st_cl4,sap1)
arm2.add_item_to_arm_map(st_cl3,sap1)
arm2.add_item_to_arm_map(st_cl2,sap1)
arm2.add_item_to_arm_map(st_cl5,sap1)
arm3 = StudyArm(name='Arm 3')
arm3.group_size=2
arm3.source_type=Characteristic(category=genotype_cat,
value=genotype_value1
)
arm3.add_item_to_arm_map(st_cl1,sap1)
arm3.add_item_to_arm_map(st_cl2,sap1)
arm3.add_item_to_arm_map(st_cl3,sap1)
arm3.add_item_to_arm_map(st_cl4,sap1)
arm3.add_item_to_arm_map(st_cl5,sap1)
arm4 = StudyArm(name='Arm 4')
arm4.group_size=2
arm4.source_type=Characteristic(category=genotype_cat,
value=genotype_value2)
arm4.add_item_to_arm_map(st_cl1,sap1)
arm4.add_item_to_arm_map(st_cl4,None)
arm4.add_item_to_arm_map(st_cl3,sap1)
arm4.add_item_to_arm_map(st_cl2,None)
arm4.add_item_to_arm_map(st_cl5,sap1)
14. We can now create the ISA Study Design object, which will receive the Arms defined by the user.¶
study_design_final= StudyDesign(name='trial design #1')
# print(sd)
# Adding a study arm to the study design object.
study_design_final.add_study_arm(arm1)
study_design_final.add_study_arm(arm2)
study_design_final.add_study_arm(arm3)
study_design_final.add_study_arm(arm4)
study_finale = study_design_final.generate_isa_study()
investigation1.studies.append(study_finale)
# print(investigation1.studies[0].name)
# Let's now serialize the ISA study design to JSON
from isatools.create.model import StudyDesignEncoder
f=json.dumps(study_design_final, cls=StudyDesignEncoder, sort_keys=True, indent=4, separators=(',', ': '))
final_dir = os.path.abspath(os.path.join('notebook-output', 'isa-study-custom-assay-light-sensitivity'))
with open(os.path.join(final_dir,'./light-sensitivity-study_design_final.json'), 'w') as isa_sdf_jf:
json.dump(json.loads(f), isa_sdf_jf)
# print(json.dumps(investigation, cls=ISAJSONEncoder, sort_keys=True, indent=4, separators=(',', ': ')))
from isatools import isatab
isatab.dump(investigation1, final_dir)
from isatools.isatab import dump_tables_to_dataframes as dumpdf
dataframes = dumpdf(investigation)
2021-07-21 17:43:54,822 [INFO]: isatab.py(_all_end_to_end_paths:1131) >> [3, 4, 5, 6]
2021-07-21 17:43:54,828 [WARNING]: isatab.py(write_study_table_files:1194) >> [8, 7, 3, 10, 9, 12, 11, 14, 13, 16, 15, 18, 17, 20, 19, 22, 21, 24, 23, 26, 25, 28, 27, 30, 29, 32, 31, 34, 33, 36, 35, 38, 37, 40, 39, 42, 41, 44, 43, 46, 45, 48, 47, 4, 50, 49, 52, 51, 54, 53, 56, 55, 58, 57, 60, 59, 62, 61, 64, 63, 66, 65, 68, 67, 70, 69, 72, 71, 74, 73, 76, 75, 78, 77, 80, 79, 82, 81, 84, 83, 86, 85, 88, 87, 5, 90, 89, 92, 91, 94, 93, 96, 95, 98, 97, 100, 99, 102, 101, 104, 103, 106, 105, 108, 107, 110, 109, 112, 111, 114, 113, 116, 115, 118, 117, 120, 119, 122, 121, 124, 123, 126, 125, 128, 127, 6, 130, 129, 132, 131, 134, 133, 136, 135, 138, 137, 140, 139, 142, 141, 144, 143, 146, 145, 148, 147, 150, 149]
2021-07-21 17:43:54,829 [INFO]: isatab.py(_longest_path_and_attrs:1091) >> [[3, 8, 7], [3, 10, 9], [3, 12, 11], [3, 14, 13], [3, 16, 15], [3, 18, 17], [3, 20, 19], [3, 22, 21], [3, 24, 23], [3, 26, 25], [3, 28, 27], [3, 30, 29], [3, 32, 31], [3, 34, 33], [3, 36, 35], [3, 38, 37], [3, 40, 39], [3, 42, 41], [3, 44, 43], [3, 46, 45], [4, 48, 47], [4, 50, 49], [4, 52, 51], [4, 54, 53], [4, 56, 55], [4, 58, 57], [4, 60, 59], [4, 62, 61], [4, 64, 63], [4, 66, 65], [4, 68, 67], [4, 70, 69], [4, 72, 71], [4, 74, 73], [4, 76, 75], [4, 78, 77], [4, 80, 79], [4, 82, 81], [4, 84, 83], [4, 86, 85], [5, 88, 87], [5, 90, 89], [5, 92, 91], [5, 94, 93], [5, 96, 95], [5, 98, 97], [5, 100, 99], [5, 102, 101], [5, 104, 103], [5, 106, 105], [5, 108, 107], [5, 110, 109], [5, 112, 111], [5, 114, 113], [5, 116, 115], [5, 118, 117], [5, 120, 119], [5, 122, 121], [5, 124, 123], [5, 126, 125], [6, 130, 129], [6, 132, 131], [6, 134, 133], [6, 136, 135], [6, 138, 137], [6, 140, 139], [6, 142, 141], [6, 144, 143], [6, 146, 145], [6, 148, 147], [6, 150, 149], [6, 128, 127]]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
/var/folders/5n/rl6lqnks4rqb59pbtpvvntqw0000gr/T/ipykernel_17990/2479725034.py in <module>
1 # print(json.dumps(investigation, cls=ISAJSONEncoder, sort_keys=True, indent=4, separators=(',', ': ')))
2 from isatools import isatab
----> 3 isatab.dump(investigation1, final_dir)
4
5 from isatools.isatab import dump_tables_to_dataframes as dumpdf
~/.pyenv/versions/3.9.0/envs/isa-api-py39/lib/python3.9/site-packages/isatools/isatab.py in dump(isa_obj, output_path, i_file_name, skip_dump_tables, write_factor_values_in_assay_table)
1047 pass
1048 else:
-> 1049 write_study_table_files(investigation, output_path)
1050 write_assay_table_files(
1051 investigation, output_path, write_factor_values_in_assay_table)
~/.pyenv/versions/3.9.0/envs/isa-api-py39/lib/python3.9/site-packages/isatools/isatab.py in write_study_table_files(inv_obj, output_dir)
1295 fvlabel = "{0}.Factor Value[{1}]".format(
1296 olabel, fv.factor_name.name)
-> 1297 write_value_columns(df_dict, fvlabel, fv)
1298 """if isinstance(pbar, ProgressBar):
1299 pbar.finish()"""
~/.pyenv/versions/3.9.0/envs/isa-api-py39/lib/python3.9/site-packages/isatools/isatab.py in write_value_columns(df_dict, label, x)
1715 if isinstance(x.value, (int, float)) and x.unit:
1716 if isinstance(x.unit, OntologyAnnotation):
-> 1717 df_dict[label][-1] = x.value
1718 df_dict[label + ".Unit"][-1] = x.unit.term
1719 df_dict[label + ".Unit.Term Source REF"][-1] = \
KeyError: 'Sample Name.0.Factor Value[DURATION]'
About this notebook¶
authors: philippe.rocca-serra@oerc.ox.ac.uk, massimiliano.izzo@oerc.ox.ac.uk
license: CC-BY 4.0
support: isatools@googlegroups.com
issue tracker: https://github.com/ISA-tools/isa-api/issues