def __init__(self, study, config_properties=None):
self.study = study
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.snp_dir = self.properties.snp_dir
assert study is not None, "You must specify a study to delete a study!"
def __init__(self,
snp,
start,
size,
config_properties=None,
chromosome=None):
self.snp = snp
self.chromosome = chromosome
self.start = start
self.size = size
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.chr_dir = self.properties.chr_dir
self.snp_dir = self.properties.snp_dir
self.bp_step = self.properties.bp_step
self.datasets = utils.create_dictionary_of_empty_dsets(TO_QUERY_DSETS)
self.index_marker = 0
if chromosome is None:
self.service = self._calculate_snp_service()
else:
self.service = self._get_snp_service()
def __init__(self, config_properties=None):
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.study_dir = self.properties.study_dir
self.trait_dir = self.properties.trait_dir
self.sqlite_db = self.properties.sqlite_path
self.trait_file = os.path.join(self.search_path, self.trait_dir,
"file_phen_meta.sqlite")
def __init__(self, start, size, config_properties=None):
self.starting_point = start
self.start = start
self.size = size
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.trait_dir = self.properties.trait_dir
self.datasets = utils.create_dictionary_of_empty_dsets(TO_QUERY_DSETS)
# index marker will be returned along with the datasets
# it is the number that when added to the 'start' value that we started the query with
# will pinpoint where the next search needs to continue from
self.index_marker = self.search_traversed = 0
def __init__(self,
start,
size,
pval_interval=None,
config_properties=None,
study=None,
chromosome=None,
bp_interval=None,
trait=None,
gene=None,
tissue=None,
snp=None,
quant_method=None,
qtl_group=None,
paginate=True):
self.starting_point = start
self.start = start
self.max_size = 1000
self.size = size if int(size) <= self.max_size else self.max_size
self.study = study
self.pval_interval = pval_interval
self.chromosome = chromosome
self.bp_interval = bp_interval
self.trait = trait
self.gene = gene
self.tissue = tissue if qtl_group is None else None # doesn't make sense to allow tissue and qtl group to be specified
self.snp = snp
self.qtl_group = qtl_group
self.quant_method = quant_method if quant_method else "ge"
self.paginate = paginate
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.study_dir = self.properties.study_dir
self.chr_dir = self.properties.chr_dir
self.trait_dir = self.properties.trait_dir
self.database = self.properties.sqlite_path
self.snpdb = self.properties.snpdb
self.trait_file = os.path.join(self.search_path, self.trait_dir,
"file_phen_meta.sqlite")
self.hdfs = []
self.search_dir = None
self.datasets = None #utils.create_dictionary_of_empty_dsets(TO_QUERY_DSETS)
# index marker will be returned along with the datasets
# it is the number that when added to the 'start' value that we started the query with
# will pinpoint where the next search needs to continue from
self.index_marker = self.search_traversed = 0
self.df = pd.DataFrame()
logger.debug("quant: ".format(self.quant_method))
def __init__(self, chromosome, start, size, config_properties=None):
self.chromosome = chromosome
self.start = start
self.size = size
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.chr_dir = self.properties.chr_dir
self.datasets = utils.create_dictionary_of_empty_dsets(TO_QUERY_DSETS)
self.index_marker = 0
self.h5file = fsutils.create_h5file_path(path=self.search_path, dir_name=self.chr_dir, file_name=chromosome)
if not os.path.isfile(self.h5file):
raise NotFoundError("Chromosome " + str(chromosome))
self.service = chromosome_service.ChromosomeService(self.h5file)
def __init__(self, trait, start, size, config_properties=None):
self.trait = trait
self.start = start
self.size = size
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.trait_dir = self.properties.trait_dir
self.datasets = utils.create_dictionary_of_empty_dsets(TO_QUERY_DSETS)
# index marker will be returned along with the datasets
# it is the number that when added to the 'start' value that we started the query with
# will pinpoint where the next search needs to continue from
self.index_marker = 0
self.h5file = fsutils.create_h5file_path(self.search_path,
dir_name=self.trait_dir,
file_name=trait)
if not os.path.isfile(self.h5file):
raise NotFoundError("Trait " + trait)
self.service = study_service.StudyService(self.h5file)
def __init__(self, study, config_properties=None):
self.properties = properties_handler.get_properties(config_properties)
self.study = study
def __init__(self, config_properties=None):
self.properties = properties_handler.get_properties(config_properties)
self.search_path = properties_handler.get_search_path(self.properties)
self.trait_dir = self.properties.trait_dir
