def add_organism_details(itm_i, itm_s, dj_organism):
ncbitaxon = itm.OntologySource(name='NCBITaxon',
description="NCBI Taxonomy")
itm_i.ontology_source_references.append(ncbitaxon)
organism = itm.OntologyAnnotation(term_source=ncbitaxon)
organism.term = dj_organism.ontology_term
organism.term_accession = dj_organism.ontology_accession
itm_s.design_descriptors.append(organism)
return organism
def add_organism_part_sample(dj_ss):
if dj_ss.organism_part:
dj_org_ont = dj_ss.organism_part.ontologyterm
src = itm.OntologySource(name=dj_org_ont.ontology_prefix,
description=dj_org_ont.ontology_name)
val = itm.OntologyAnnotation(term=dj_org_ont.name,
term_source=src,
term_accession=dj_org_ont.iri)
else:
val = itm.OntologyAnnotation(term='',
term_source='',
term_accession='')
return itm.Characteristic(category=itm.OntologyAnnotation(
term="Organism part",
term_source="NCIT",
term_accession="http://purl.obolibrary.org/obo/NCIT_C103199"),
value=val)
def new_ontology_source():
'''Create a new Ontology Source.
'''
form = OntologySourceForm(request.form)
if form.validate_on_submit():
new_source = isa.OntologySource(name=form.name.data,
description=form.description.data)
json_source = jsonify_isa_object(new_source)
source_dict = json.loads(json_source)
mongo.db.ontology_sources.insert_one(source_dict)
flash('Created a new ontology source.', 'success')
return redirect(url_for("user.ontologies"))
return render_template('user/create_ontology_source.html', form=form)
def add_lcms_untargeted_meta(itm_i, itm_s, msms_performed=True):
obi = itm.OntologySource(name='CHMO',
description="Chemical Methods Ontology")
itm_i.ontology_source_references.append(obi)
uplcms = itm.OntologyAnnotation(term_source=obi)
uplcms.term = "ultra-performance liquid chromatography-mass spectrometry"
uplcms.term_accession = "http://purl.obolibrary.org/obo/CHMO_0000715"
itm_s.design_descriptors.append(uplcms)
if msms_performed:
msms = itm.OntologyAnnotation(term_source=obi)
msms.term = "tandem mass spectrometry"
msms.term_accession = "http://purl.obolibrary.org/obo/CHMO_0000575"
itm_s.design_descriptors.append(msms)
untargeted_met = itm.OntologyAnnotation()
untargeted_met.term = "untargeted metabolites"
itm_s.design_descriptors.append(untargeted_met)
return itm_i, itm_s
def create_isa_files(investigation_id):
# Create investigation
dj_i = Investigation.objects.get(pk=investigation_id)
itm_i = itm.Investigation(filename="i_investigation.txt")
itm_i.identifier = "i1"
itm_i.title = dj_i.name
itm_i.description = dj_i.description
################################################################################################################
# STUDIES
################################################################################################################
itm_sample_d = {} # to traceback from django samples
for i, dj_s in enumerate(dj_i.study_set.all()):
itm_s = itm.Study(filename="s_study.txt")
itm_s.identifier = "s" + str(i)
itm_s.title = dj_s.name
itm_s.description = dj_s.description
itm_s.grant_number = dj_s.grant_number
itm_s.public_release_date = dj_s.public_release_date.strftime(
"%Y-%m-%d") if dj_s.public_release_date else ''
itm_s.submission_date = dj_s.submission_date.strftime(
"%Y-%m-%d") if dj_s.submission_date else ''
itm_i.studies.append(itm_s)
itm_i, itm_s = add_lcms_untargeted_meta(itm_i,
itm_s,
msms_performed=True)
# Add study samples
# loop through the study samples
################################################################################################################
# STUDY SAMPLES
################################################################################################################
for j, dj_ss in enumerate(dj_s.studysample_set.all()):
# We are saying that each sample is derived from a different source material, this might not be true for
# for all cases but should be fine for the resulting ISA-Tab structure for MetaboLights
source = itm.Source(name='{} source'.format(dj_ss.sample_name))
itm_s.sources.append(source)
# Sample material from the source
itm_sample = itm.Sample(name=dj_ss.sample_name,
derives_from=source)
#=====================
# Add organism for sample
#=====================
if dj_ss.organism:
dj_org_ont = dj_ss.organism.ontologyterm
source = check_ontology_source(itm_i, dj_org_ont.ontology_name)
if not source:
source = itm.OntologySource(
name=dj_org_ont.ontology_prefix,
description=dj_org_ont.ontology_name)
itm_i.ontology_source_references.append(source)
val = itm.OntologyAnnotation(term=dj_org_ont.name,
term_source=source,
term_accession=dj_org_ont.iri)
else:
val = itm.OntologyAnnotation(term='',
term_source='',
term_accession='')
char = itm.Characteristic(category=itm.OntologyAnnotation(
term="Organism",
term_source="NCIT",
term_accession="http://purl.obolibrary.org/obo/NCIT_C14250"),
value=val)
itm_sample.characteristics.append(char)
# =====================
# Add organism part
# =====================
if dj_ss.organism_part:
dj_org_ont = dj_ss.organism_part.ontologyterm
source = check_ontology_source(itm_i, dj_org_ont.ontology_name)
if not source:
source = itm.OntologySource(
name=dj_org_ont.ontology_prefix,
description=dj_org_ont.ontology_name)
itm_i.ontology_source_references.append(source)
val = itm.OntologyAnnotation(term=dj_org_ont.name,
term_source=source,
term_accession=dj_org_ont.iri)
else:
val = itm.OntologyAnnotation(term='',
term_source='',
term_accession='')
char = itm.Characteristic(category=itm.OntologyAnnotation(
term="Organism part",
term_source="NCIT",
term_accession="http://purl.obolibrary.org/obo/NCIT_C103199"),
value=val)
# Add organism part for sample (e.g. foot, eye, leg, whole organism...)
itm_sample.characteristics.append(char)
# Potential to add technical replicates (repeat extractions of the same material but
# to confusing to use for DMA because we have extractions at different points (Liquid Extraction, SPE and
# Fractionation
itm_s.samples.append(itm_sample)
itm_sample_d[dj_ss.id] = itm_sample
# Create sample collection protocol (we just use 1 for all samples for the time being) but should technically
# be divided into groups (if resulting ISA-Tab for MetaboLights is the same then we can just leave as is)
sample_collection_protocol = itm.Protocol(
name="sample collection",
protocol_type=itm.OntologyAnnotation(term="sample collection"))
itm_s.protocols.append(sample_collection_protocol)
sample_collection_process = itm.Process(
executes_protocol=sample_collection_protocol)
# Next, we link our materials to the Process. In this particular case, we are describing a sample collection
# process that takes one source material, and produces three different samples.
#
# (daphnia magna source) -> (sample collection) -> [(daphnia_material0-0), (daphnia_material0-1), (daphnia_material0-2)]
# (solvent blank source) -> (sample collection) -> [(blank_material1-0), (blank_material1-1), (sample_material1-2)]
for src in itm_s.sources:
sample_collection_process.inputs.append(src)
for sam in itm_s.samples:
sample_collection_process.outputs.append(sam)
# Finally, attach the finished Process object to the study process_sequence. This can be done many times to
# describe multiple sample collection events.
itm_s.process_sequence.append(sample_collection_process)
################################################################################################################
# ASSAYS
################################################################################################################
# get dictionary of Django protocols
dj_p = {'ex': {}, 'spe': {}, 'chr': {}, 'meas': {}}
for dj_a in dj_s.assay_set.all():
for dj_ad in dj_a.assaydetail_set.all():
ex = dj_ad.extractionprocess.extractionprotocol
dj_p['ex'][ex.id] = ex
spe = dj_ad.speprocess.speprotocol
dj_p['spe'][spe.id] = spe
chrom = dj_ad.chromatographyprocess.chromatographyprotocol
dj_p['chr'][chrom.id] = chrom
meas = dj_ad.measurementprocess.measurementprotocol
dj_p['meas'][meas.id] = meas
# Create isa tab protocols
itm_p = {'ex': {}, 'spe': {}, 'chr': {}, 'meas': {}}
# sequencing_protocol = itm.Protocol(name='sequencing', protocol_type=itm.OntologyAnnotation(term="material sequencing"))
# itm_s.protocols.append(sequencing_protocol)
for k, dj_ex in six.iteritems(dj_p['ex']):
if dj_ex.name:
nm = dj_ex.name
else:
nm = dj_ex.extractiontype.type
#===========================================
# Get extraction protocols
#===========================================
source = check_ontology_source(itm_i, 'CHMO')
extraction_protocol = itm.Protocol(
name='Extraction {}'.format(nm),
protocol_type=itm.OntologyAnnotation(term="Extraction"),
)
param = itm.ProtocolParameter(parameter_name=itm.OntologyAnnotation(
term="Derivatization",
term_source=source,
term_accession='http://purl.obolibrary.org/obo/CHMO_0001485'))
extraction_protocol.parameters.append(param)
itm_s.protocols.append(extraction_protocol)
itm_p['ex'][k] = extraction_protocol
for k, dj_spe in six.iteritems(dj_p['spe']):
if dj_spe.name:
nm = dj_spe.name
else:
nm = dj_spe.spetype.type
#===========================================
# Get chromatography protocols
#===========================================
spe_protocol = itm.Protocol(
name='Solid Phase Extraction {}'.format(nm),
protocol_type=itm.OntologyAnnotation(
term="Solid Phase Extraction"),
components=itm.OntologyAnnotation(term=nm),
description=dj_spe.description)
itm_s.protocols.append(spe_protocol)
itm_p['spe'][k] = spe_protocol
for k, dj_chr in six.iteritems(dj_p['chr']):
#===========================================
# Get chromatography protocols
#===========================================
chromatography_protocol = itm.Protocol(
name='Chromatography {}'.format(dj_chr.name),
protocol_type=itm.OntologyAnnotation(term="Chromatography"))
itm_s.protocols.append(chromatography_protocol)
itm_p['chr'][k] = chromatography_protocol
for k, dj_meas in six.iteritems(dj_p['meas']):
#===========================================
# Get measurment protocols (just mass spec for now)
#===========================================
if dj_meas.name:
nm = dj_meas.name
else:
nm = dj_meas.measurementtechnique.type
mass_spec_protocol = itm.Protocol(
name='Mass spectrometry {}'.format(nm),
protocol_type=itm.OntologyAnnotation(term="Mass spectrometry"))
itm_s.protocols.append(mass_spec_protocol)
itm_p['meas'][k] = mass_spec_protocol
for dj_a in dj_s.assay_set.all():
itm_a = itm.Assay(filename="a_assay_{}.txt".format(dj_a.name))
# go through each details (which is linked to all the revelant process)
for dj_ad in dj_a.assaydetail_set.all():
####################################
# Get extraction
####################################
itm_ex_prot = itm_p['ex'][
dj_ad.extractionprocess.extractionprotocol.id]
extraction_process = itm.Process(executes_protocol=itm_ex_prot)
extraction_process.name = "extract-process-{}".format(
dj_ad.code_field)
material = itm.Material(
name="extract-{}".format(dj_ad.code_field))
material.type = "Extract Name"
extraction_process.outputs.append(material)
############################################################
##### IMPORTANT: WE add the sample input here! #############
itm_samplei = itm_sample_d[dj_ad.studysample_id]
extraction_process.inputs.append(itm_samplei)
####################################
# Get SPE
####################################
if dj_ad.speprocess:
itm_spe_prot = itm_p['spe'][
dj_ad.speprocess.speprotocol.id]
spe_process = itm.Process(executes_protocol=itm_spe_prot)
spe_process.name = "spe-process-{}".format(
dj_ad.code_field)
spe_process.inputs.append(extraction_process.outputs[0])
material = itm.Material(
name="SPE-Eluent-{}".format(dj_ad.code_field))
material.type = "Extract Name"
spe_process.outputs.append(material)
####################################
# Get chromatography
####################################
itm_chr_prot = itm_p['chr'][
dj_ad.chromatographyprocess.chromatographyprotocol.id]
chr_process = itm.Process(executes_protocol=itm_chr_prot)
chr_process.name = "chr-process-{}".format(dj_ad.code_field)
if dj_ad.speprocess:
chr_process.inputs.append(spe_process.outputs[0])
else:
chr_process.inputs.append(extraction_process.outputs[0])
material = itm.Material(
name="Chromatography-Eluent-{}".format(dj_ad.code_field))
material.type = "Extract Name"
chr_process.outputs.append(material)
####################################
# Get measurements (mass spec only)
####################################
itm_meas_prot = itm_p['meas'][
dj_ad.measurementprocess.measurementprotocol.id]
meas_process = itm.Process(executes_protocol=itm_meas_prot)
meas_process.name = "meas-process-{}".format(dj_ad.code_field)
meas_process.inputs.append(chr_process.outputs[0])
# get output file
for file_details in dj_ad.assayrun_set.all().values(
'run__mfile', 'run__mfile__original_filename'):
datafile = itm.DataFile(
filename=file_details['run__mfile__original_filename'],
label="Raw Data File")
meas_process.outputs.append(datafile)
itm_a.data_files.append(datafile)
if dj_ad.speprocess:
itm.plink(extraction_process, spe_process)
itm.plink(spe_process, chr_process)
else:
itm.plink(extraction_process, chr_process)
itm.plink(chr_process, meas_process)
itm_a.samples.append(itm_samplei)
itm_a.other_material.append(material)
itm_a.process_sequence.append(extraction_process)
if dj_ad.speprocess:
itm_a.process_sequence.append(spe_process)
itm_a.process_sequence.append(chr_process)
itm_a.process_sequence.append(meas_process)
itm_a.measurement_type = itm.OntologyAnnotation(
term="gene sequencing")
itm_a.technology_type = itm.OntologyAnnotation(
term="nucleotide sequencing")
itm_s.assays.append(itm_a)
# Note we haven't added factors yet
return itm_i, json.dumps(itm_i,
cls=ISAJSONEncoder,
sort_keys=True,
indent=4,
separators=(',', ': '))