def make_widgets(filter_manager, include_dataset_specific=False):
base_widgets = {
'dataset': FilterWidget(
'Mutation dataset', 'radio',
filter=filter_manager.filters['Mutation.sources'],
labels=create_dataset_labels(),
disabled_label='All datasets'
),
'ptm_type': FilterWidget(
'Type of PTM site', 'radio',
filter=filter_manager.filters['Site.types'],
disabled_label='all sites'
),
'has_ptm': FilterWidget(
'Genes with PTM mutations only', 'checkbox',
filter=filter_manager.filters['Gene.has_ptm_muts'],
disabled_label='all genes',
labels=['Genes with PTM mutations only']
),
'is_kinase': FilterWidget(
'Genes of known kinases', 'checkbox',
filter=filter_manager.filters['Gene.is_known_kinase'],
labels=['Genes of known kinases only']
),
}
if include_dataset_specific:
dataset_specific = create_dataset_specific_widgets(
None,
filter_manager.filters,
population_widgets=False
)
base_widgets['dataset_specific'] = dataset_specific
return base_widgets
def make_widgets(filter_manager):
return {
'proteins': {
'ptm':
FilterWidget(
'Show only proteins with PTM mutations',
'checkbox',
filter=filter_manager.filters['Protein.has_ptm_mutations'],
class_name='pull-right'),
'feature':
FilterWidget('Search by',
'checkbox_multiple',
filter=filter_manager.filters['Feature.name'],
labels=[
engine.pretty_name
for engine in advanced_search_engines.values()
],
all_selected_label='All features',
class_name='checkboxes-inline')
},
'mutations': [
FilterWidget(
'Show all mutations (by default only PTM mutations are shown)',
'checkbox',
filter=filter_manager.filters['Mutation.is_ptm'],
class_name='pull-right'),
]
}
def _create_option_widgets(self, filter_manager):
return [
FilterWidget(
'Show sites',
'binary',
filter=filter_manager.filters['JavaScript.show_sites']),
FilterWidget(
'Clone kinases by site',
'binary',
filter=filter_manager.filters['JavaScript.clone_by_site']),
FilterWidget(
'Prevent drug overlapping',
'binary',
filter=filter_manager.filters['JavaScript.collide_drugs']),
]
def create_widgets(protein, filters_by_id, custom_datasets_names=None):
"""Widgets to be displayed on a bar above visualisation."""
return {
'dataset':
FilterWidget('Mutation dataset',
'radio',
filter=filters_by_id['Mutation.sources'],
labels=cached_queries.dataset_labels,
class_name='dataset-widget'),
'custom_dataset':
FilterWidget('Custom mutation dataset',
'radio',
filter=filters_by_id['UserMutations.sources'],
labels=custom_datasets_names),
'dataset_specific':
create_dataset_specific_widgets(protein, filters_by_id),
'is_ptm':
FilterWidget('PTM mutations only',
'checkbox',
filter=filters_by_id['Mutation.is_ptm'],
disabled_label='all mutations',
labels=['PTM mutations only']),
'ptm_type':
FilterWidget('Type of PTM site',
'radio',
filter=filters_by_id['Site.types'],
disabled_label='Any site',
hierarchy={
site_type.name: site_type.sub_types
for site_type in cached_queries.site_types
if site_type.sub_types
}),
'other': [
FilterWidget(
'Drug group',
'checkbox_multiple',
filter=filters_by_id['Drug.groups.name'],
labels=[group.title() for group in cached_queries.drug_groups],
)
]
}
def create_dataset_specific_widgets(protein,
filters_by_id,
population_widgets=True):
cancer_codes_mc3 = protein.cancer_codes(MC3Mutation) if protein else []
widgets = [
FilterWidget('Cancer type',
'checkbox_multiple',
filter=filters_by_id['Mutation.mc3_cancer_code'],
labels=cached_queries.all_cancer_names,
choices=cancer_codes_mc3,
all_selected_label='Any cancer type'),
FilterWidget('Clinical significance',
'checkbox_multiple',
filter=filters_by_id['Mutation.sig_code'],
all_selected_label='Any clinical significance class',
labels=ClinicalData.significance_codes.values()),
FilterWidget('Disease name',
'checkbox_multiple',
filter=filters_by_id['Mutation.disease_name'],
all_selected_label='Any disease name')
]
if population_widgets:
widgets += [
FilterWidget('Ethnicity',
'checkbox_multiple',
filter=filters_by_id['Mutation.populations_1KG'],
labels=populations_labels(
The1000GenomesMutation.populations),
all_selected_label='Any ethnicity'),
FilterWidget('Ethnicity',
'checkbox_multiple',
filter=filters_by_id['Mutation.populations_ESP6500'],
labels=populations_labels(
ExomeSequencingMutation.populations),
all_selected_label='Any ethnicity')
]
return widgets