class StarQualityMetric(QualityMetric):
item_type = 'star_quality_metric'
schema = load_schema('encoded:schemas/star_quality_metric.json')
class SamtoolsStatsQualityMetric(QualityMetric):
item_type = 'samtools_stats_quality_metric'
schema = load_schema('encoded:schemas/samtools_stats_quality_metric.json')
class Document(ItemWithAttachment, Item):
item_type = 'document'
schema = load_schema('encoded:schemas/document.json')
embedded = ['lab', 'award', 'submitted_by']
class PhantompeaktoolsSppQualityMetric(QualityMetric):
item_type = 'phantompeaktools_spp_quality_metric'
schema = load_schema(
'encoded:schemas/phantompeaktools_spp_quality_metric.json')
class BigwigcorrelateQualityMetric(QualityMetric):
item_type = 'bigwigcorrelate_quality_metric'
schema = load_schema('encoded:schemas/bigwigcorrelate_quality_metric.json')
class EdwbamstatsQualityMetric(QualityMetric):
item_type = 'edwbamstats_quality_metric'
schema = load_schema('encoded:schemas/edwbamstats_quality_metric.json')
class EdwcomparepeaksQualityMetric(QualityMetric):
item_type = 'edwcomparepeaks_quality_metric'
schema = load_schema('encoded:schemas/edwcomparepeaks_quality_metric.json')
class Encode2ChipSeqQualityMetric(QualityMetric):
item_type = 'encode2_chipseq_quality_metric'
schema = load_schema('encoded:schemas/encode2_chipseq_quality_metric.json')
class Source(Item):
item_type = 'source'
schema = load_schema('encoded:schemas/source.json')
name_key = 'name'
class Treatment(Item):
item_type = 'treatment'
schema = load_schema('encoded:schemas/treatment.json')
class Organism(Item):
item_type = 'organism'
schema = load_schema('encoded:schemas/organism.json')
name_key = 'name'
class Award(Item):
item_type = 'award'
schema = load_schema('encoded:schemas/award.json')
name_key = 'name'
embedded = ['pi']
class Lab(Item):
item_type = 'lab'
schema = load_schema('encoded:schemas/lab.json')
name_key = 'name'
embedded = ['awards']
class FastqcQualityMetric(QualityMetric):
item_type = 'fastqc_quality_metric'
schema = load_schema('encoded:schemas/fastqc_quality_metric.json')
class HotspotQualityMetric(QualityMetric):
item_type = 'hotspot_quality_metric'
schema = load_schema('encoded:schemas/hotspot_quality_metric.json')
class BismarkQualityMetric(QualityMetric):
item_type = 'bismark_quality_metric'
schema = load_schema('encoded:schemas/bismark_quality_metric.json')
class IdrSummaryQualityMetric(QualityMetric):
item_type = 'idr_summary_quality_metric'
schema = load_schema('encoded:schemas/idr_summary_quality_metric.json')
class ChipSeqFilterQualityMetric(QualityMetric):
item_type = 'chipseq_filter_quality_metric'
schema = load_schema('encoded:schemas/chipseq_filter_quality_metric.json')
class MadQualityMetric(QualityMetric):
item_type = 'mad_quality_metric'
schema = load_schema('encoded:schemas/mad_quality_metric.json')
class DnasePeakQualityMetric(QualityMetric):
item_type = 'dnase_peak_quality_metric'
schema = load_schema('encoded:schemas/dnase_peak_quality_metric.json')
class PbcQualityMetric(QualityMetric):
item_type = 'pbc_quality_metric'
schema = load_schema('encoded:schemas/pbc_quality_metric.json')
class WormDonor(Donor):
item_type = 'worm_donor'
schema = load_schema('encoded:schemas/worm_donor.json')
embedded = ['organism', 'constructs', 'constructs.target']
class Dataset(Item):
item_type = 'dataset'
schema = load_schema('encoded:schemas/dataset.json')
embedded = [
'files', 'files.replicate', 'files.replicate.experiment',
'files.replicate.experiment.lab', 'files.replicate.experiment.target',
'files.submitted_by', 'files.lab', 'revoked_files',
'revoked_files.replicate', 'revoked_files.replicate.experiment',
'revoked_files.replicate.experiment.lab',
'revoked_files.replicate.experiment.target',
'revoked_files.submitted_by', 'contributing_files',
'contributing_files.replicate.experiment',
'contributing_files.replicate.experiment.lab',
'contributing_files.replicate.experiment.target',
'contributing_files.submitted_by', 'submitted_by', 'lab', 'award',
'documents.lab', 'documents.award', 'documents.submitted_by',
'references'
]
audit_inherit = [
'original_files',
'revoked_files',
'contributing_files',
'submitted_by',
'lab',
'award',
'documents.lab',
]
name_key = 'accession'
rev = {
'original_files': ('File', 'dataset'),
}
@calculated_property(
schema={
"title": "Original files",
"type": "array",
"items": {
"type": ['string', 'object'],
"linkFrom": "File.dataset",
},
})
def original_files(self, request, original_files):
return paths_filtered_by_status(request, original_files)
@calculated_property(
schema={
"title": "Contributing files",
"type": "array",
"items": {
"type": 'string',
"linkTo": "file",
},
})
def contributing_files(self, request, original_files, related_files,
status):
files = set(original_files + related_files)
derived_from = set()
for path in files:
properties = request.embed(path, '@@object')
derived_from.update(
paths_filtered_by_status(request,
properties.get('derived_from', [])))
outside_files = list(derived_from.difference(files))
if status in ('release ready', 'released'):
return paths_filtered_by_status(
request,
outside_files,
include=('released', ),
)
else:
return paths_filtered_by_status(
request,
outside_files,
exclude=('revoked', 'deleted', 'replaced'),
)
@calculated_property(
schema={
"title": "Files",
"type": "array",
"items": {
"type": "string",
"linkTo": "file",
},
})
def files(self, request, original_files, related_files, status):
if status in ('release ready', 'released'):
return paths_filtered_by_status(
request,
chain(original_files, related_files),
include=('released', ),
)
else:
return paths_filtered_by_status(
request,
chain(original_files, related_files),
exclude=('revoked', 'deleted', 'replaced'),
)
@calculated_property(
schema={
"title": "Revoked files",
"type": "array",
"items": {
"type": "string",
"linkTo": "file",
},
})
def revoked_files(self, request, original_files, related_files):
return [
path for path in chain(original_files, related_files)
if file_is_revoked(request, path)
]
@calculated_property(define=True,
schema={
"title": "Assembly",
"type": "array",
"items": {
"type": "string",
},
})
def assembly(self, request, original_files, related_files):
assembly = []
for path in chain(original_files, related_files):
properties = request.embed(path, '@@object')
if properties['file_format'] in ['bigWig', 'bigBed', 'narrowPeak', 'broadPeak', 'bedRnaElements', 'bedMethyl', 'bedLogR'] and \
properties['status'] in ['released']:
if 'assembly' in properties:
assembly.append(properties['assembly'])
return list(set(assembly))
@calculated_property(condition='assembly',
schema={
"title": "Hub",
"type": "string",
})
def hub(self, request):
return request.resource_path(self, '@@hub', 'hub.txt')
@calculated_property(condition='hub',
category='page',
schema={
"title": "Visualuze at UCSC",
"type": "string",
})
def visualize_ucsc(self, request, hub):
hub_url = urljoin(request.resource_url(request.root), hub)
return ('http://genome.ucsc.edu/cgi-bin/hgHubConnect'
'?hgHub_do_redirect=on'
'&hgHubConnect.remakeTrackHub=on'
'&hgHub_do_firstDb=1&hubUrl=') + quote_plus(hub_url, ':/@')
