def search_chromosome(self, study=None, pval_interval=None):
logger.info("Searching for chromosome %s", str(self.chromosome))
max_size = self.service.get_chromosome_size(chromosome=self.chromosome)
method_arguments = {'chromosome': self.chromosome}
restrictions = {'pval_interval': pval_interval, 'study': study}
return search.general_search(search_obj=self, max_size=max_size,
arguments=method_arguments, restriction_dictionary=restrictions)
def search_chromosome_block(self, bp_interval, study=None, pval_interval=None):
logger.info("Searching for chromosome %s / block floor %s, block ceil %s", str(self.chromosome),
str(bp_interval.floor()), str(bp_interval.ceil()))
max_size = self.service.get_block_range_size(chromosome=self.chromosome, bp_interval=bp_interval)
method_arguments = {'chromosome': self.chromosome, 'bp_interval': bp_interval}
restrictions = {'pval_interval': pval_interval, 'study': study}
return search.general_search(search_obj=self, max_size=max_size,
arguments=method_arguments, restriction_dictionary=restrictions)
def search_snp(self, study=None, pval_interval=None):
logger.info("Searching for variant %s", self.snp)
max_size = self.service.get_snp_size(self.snp)
method_arguments = {'snp': self.snp}
restrictions = {'pval_interval': pval_interval, 'study': study}
return search.general_search(search_obj=self,
max_size=max_size,
arguments=method_arguments,
restriction_dictionary=restrictions)
def search_trait(self, pval_interval=None):
"""
Search for the data of the TraitSearch object's trait
:param pval_interval: optional p-value interval of type FloatInterval
:return: a tuple (datasets, index_marker) where 'datasets' is a dictionary with the names of the datasets and
the data to be returned (the result of the query after applying restrictions) and index_marker is an integer indicating
up to where the query went in the dataset so that the next query can calculate it's next start base on the index_marker.
"""
logger.info("Searching for trait %s with pval_interval %s", self.trait,
str(pval_interval))
method_arguments = {'trait': self.trait}
restrictions = {'pval_interval': pval_interval}
return search.general_search(search_obj=self,
max_size=self.max_size_of_trait,
arguments=method_arguments,
restriction_dictionary=restrictions)
def search_study(self, study, pval_interval=None):
"""
Search for the data of a study that lives under the StudySearch object's trait
:param study: name of the study we are searching for (str)
:param pval_interval: optional p-value interval of type FloatInterval
:return: a tuple (datasets, index_marker) where 'datasets' is a dictionary with the names of the datasets and
the data to be returned (the result of the query after applying restrictions) and index_marker is an integer indicating
up to where the query went in the dataset so that the next query can calculate it's next start base on the index_marker.
"""
logger.info("Searching for study %s with pval_interval %s", study,
str(pval_interval))
method_arguments = {'trait': self.trait, 'study': study}
total_study_size = self.service.get_study_size(self.trait, study)
restrictions = {'pval_interval': pval_interval}
return search.general_search(search_obj=self,
max_size=total_study_size,
arguments=method_arguments,
restriction_dictionary=restrictions)