"Base Dataset class ..." import math import collections from redis import Redis from gn2.base import species from gn2.utility import chunks from gn2.utility.tools import get_setting from gn3.monads import MonadicDict, query_sql from pymonad.maybe import Maybe, Nothing from .datasetgroup import DatasetGroup from gn2.wqflask.database import database_connection from gn2.utility.db_tools import escape, mescape, create_in_clause from .utils import fetch_cached_results, cache_dataset_results class DataSet: """ DataSet class defines a dataset in webqtl, can be either Microarray, Published phenotype, genotype, or user input dataset(temp) """ def __init__(self, name, get_samplelist=True, group_name=None, redis_conn=Redis()): assert name, "Need a name" self.name = name self.id = None self.shortname = None self.fullname = None self.type = None self.data_scale = None # ZS: For example log2 self.accession_id = Nothing self.setup() if self.type == "Temp": # Need to supply group name as input if temp trait # sets self.group and self.group_id and gets genotype self.group = DatasetGroup(self, name=group_name) else: self.check_confidentiality() self.retrieve_other_names() # sets self.group and self.group_id and gets genotype self.group = DatasetGroup(self) self.accession_id = self.get_accession_id().value if get_samplelist == True: self.group.get_samplelist(redis_conn) self.species = species.TheSpecies(dataset=self) def as_monadic_dict(self): _result = MonadicDict({ 'name': self.name, 'shortname': self.shortname, 'fullname': self.fullname, 'type': self.type, 'data_scale': self.data_scale, 'group': self.group.name }) _result["accession_id"] = self.accession_id return _result def get_accession_id(self) -> Maybe[str]: """Get the accession_id of this dataset depending on the dataset type.""" __query = "" with database_connection(get_setting("SQL_URI")) as conn: if self.type == "Publish": __query = ( "SELECT InfoFiles.GN_AccesionId AS accession_id FROM " "InfoFiles, PublishFreeze, InbredSet " "WHERE InbredSet.Name = " f"'{conn.escape_string(self.group.name).decode()}' " "AND PublishFreeze.InbredSetId = InbredSet.Id " "AND InfoFiles.InfoPageName = PublishFreeze.Name " "AND PublishFreeze.public > 0 AND " "PublishFreeze.confidentiality < 1 " "ORDER BY PublishFreeze.CreateTime DESC" ) elif self.type == "Geno": __query = ( "SELECT InfoFiles.GN_AccesionId AS accession_id FROM " "InfoFiles, GenoFreeze, InbredSet WHERE InbredSet.Name = " f"'{conn.escape_string(self.group.name).decode()}' AND " "GenoFreeze.InbredSetId = InbredSet.Id " "AND InfoFiles.InfoPageName = GenoFreeze.ShortName " "AND GenoFreeze.public > 0 AND " "GenoFreeze.confidentiality < 1 " "ORDER BY GenoFreeze.CreateTime DESC" ) elif self.type == "ProbeSet": __query = ( "SELECT InfoFiles.GN_AccesionId AS accession_id " "FROM InfoFiles WHERE InfoFiles.InfoPageName = " f"'{conn.escape_string(self.name).decode()}'" ) else: # The Value passed is not present raise LookupError # Should there be an empty row, query_sql returns a None # value instead of yielding a value; this block # accomodates this non-intuitive edge-case for result in query_sql(conn, __query) or (): return result["accession_id"] return Nothing def retrieve_other_names(self): """This method fetches the the dataset names in search_result. If the data set name parameter is not found in the 'Name' field of the data set table, check if it is actually the FullName or ShortName instead. This is not meant to retrieve the data set info if no name at all is passed. """ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor: try: if self.type == "ProbeSet": cursor.execute( "SELECT ProbeSetFreeze.Id, ProbeSetFreeze.Name, " "ProbeSetFreeze.FullName, ProbeSetFreeze.ShortName, " "ProbeSetFreeze.DataScale, Tissue.Name " "FROM ProbeSetFreeze, ProbeFreeze, Tissue " "WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id " "AND ProbeFreeze.TissueId = Tissue.Id " "AND (ProbeSetFreeze.Name = %s OR " "ProbeSetFreeze.FullName = %s " "OR ProbeSetFreeze.ShortName = %s)", (self.name,)*3) (self.id, self.name, self.fullname, self.shortname, self.data_scale, self.tissue) = cursor.fetchone() else: self.tissue = "N/A" cursor.execute( "SELECT Id, Name, FullName, ShortName " f"FROM {self.type}Freeze " "WHERE (Name = %s OR FullName = " "%s OR ShortName = %s)", (self.name,)*3) (self.id, self.name, self.fullname, self.shortname) = cursor.fetchone() except TypeError: pass def chunk_dataset(self, dataset, n): results = {} traits_name_dict = () with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor: cursor.execute( "SELECT ProbeSetXRef.DataId,ProbeSet.Name " "FROM ProbeSet, ProbeSetXRef, ProbeSetFreeze " "WHERE ProbeSetFreeze.Name = %s AND " "ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id " "AND ProbeSetXRef.ProbeSetId = ProbeSet.Id", (self.name,)) # should cache this traits_name_dict = dict(cursor.fetchall()) for i in range(0, len(dataset), n): matrix = list(dataset[i:i + n]) trait_name = traits_name_dict[matrix[0][0]] my_values = [value for (trait_name, strain, value) in matrix] results[trait_name] = my_values return results def get_probeset_data(self, sample_list=None, trait_ids=None): # improvement of get trait data--->>> if sample_list: self.samplelist = sample_list else: self.samplelist = self.group.samplelist if self.group.parlist != None and self.group.f1list != None: if (self.group.parlist + self.group.f1list) in self.samplelist: self.samplelist += self.group.parlist + self.group.f1list with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor: cursor.execute( "SELECT Strain.Name, Strain.Id FROM " "Strain, Species WHERE Strain.Name IN " f"{create_in_clause(self.samplelist)} " "AND Strain.SpeciesId=Species.Id AND " "Species.name = %s", (self.group.species,) ) results = dict(cursor.fetchall()) sample_ids = [results[item] for item in self.samplelist] sorted_samplelist = [strain_name for strain_name, strain_id in sorted( results.items(), key=lambda item: item[1])] cursor.execute( "SELECT * from ProbeSetData WHERE StrainID IN " f"{create_in_clause(sample_ids)} AND id IN " "(SELECT ProbeSetXRef.DataId FROM " "(ProbeSet, ProbeSetXRef, ProbeSetFreeze) " "WHERE ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id " "AND ProbeSetFreeze.Name = %s AND " "ProbeSet.Id = ProbeSetXRef.ProbeSetId)", (self.name,) ) query_results = list(cursor.fetchall()) data_results = self.chunk_dataset(query_results, len(sample_ids)) self.samplelist = sorted_samplelist self.trait_data = data_results def get_trait_data(self, sample_list=None): if sample_list: self.samplelist = sample_list else: self.samplelist = self.group.samplelist if self.group.parlist != None and self.group.f1list != None: if (self.group.parlist + self.group.f1list) in self.samplelist: self.samplelist += self.group.parlist + self.group.f1list with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor: cursor.execute( "SELECT Strain.Name, Strain.Id FROM Strain, Species " f"WHERE Strain.Name IN {create_in_clause(self.samplelist)} " "AND Strain.SpeciesId=Species.Id " "AND Species.name = %s", (self.group.species,) ) results = dict(cursor.fetchall()) sample_ids = [ sample_id for sample_id in (results.get(item) for item in self.samplelist if item is not None) if sample_id is not None ] # MySQL limits the number of tables that can be used in a join to 61, # so we break the sample ids into smaller chunks # Postgres doesn't have that limit, so we can get rid of this after we transition chunk_size = 50 number_chunks = int(math.ceil(len(sample_ids) / chunk_size)) cached_results = fetch_cached_results(self.name, self.type, self.samplelist) if cached_results is None: trait_sample_data = [] for sample_ids_step in chunks.divide_into_chunks(sample_ids, number_chunks): if self.type == "Publish": dataset_type = "Phenotype" else: dataset_type = self.type temp = ['T%s.value' % item for item in sample_ids_step] if self.type == "Publish": query = "SELECT {}XRef.Id".format(escape(self.type)) else: query = "SELECT {}.Name".format(escape(dataset_type)) data_start_pos = 1 if len(temp) > 0: query = query + ", " + ', '.join(temp) query += ' FROM ({}, {}XRef, {}Freeze) '.format(*mescape(dataset_type, self.type, self.type)) for item in sample_ids_step: query += """ left join {}Data as T{} on T{}.Id = {}XRef.DataId and T{}.StrainId={}\n """.format(*mescape(self.type, item, item, self.type, item, item)) if self.type == "Publish": query += """ WHERE {}XRef.InbredSetId = {}Freeze.InbredSetId and {}Freeze.Name = '{}' and {}.Id = {}XRef.{}Id order by {}.Id """.format(*mescape(self.type, self.type, self.type, self.name, dataset_type, self.type, dataset_type, dataset_type)) else: query += """ WHERE {}XRef.{}FreezeId = {}Freeze.Id and {}Freeze.Name = '{}' and {}.Id = {}XRef.{}Id order by {}.Id """.format(*mescape(self.type, self.type, self.type, self.type, self.name, dataset_type, self.type, self.type, dataset_type)) cursor.execute(query) results = cursor.fetchall() trait_sample_data.append([list(result) for result in results]) trait_count = len(trait_sample_data[0]) self.trait_data = collections.defaultdict(list) data_start_pos = 1 for trait_counter in range(trait_count): trait_name = trait_sample_data[0][trait_counter][0] for chunk_counter in range(int(number_chunks)): self.trait_data[trait_name] += ( trait_sample_data[chunk_counter][trait_counter][data_start_pos:]) cache_dataset_results( self.name, self.type, self.samplelist, self.trait_data) else: self.trait_data = cached_results