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-rw-r--r--wqflask/base/data_set/__init__.py124
-rw-r--r--wqflask/base/data_set/dataset.py292
-rw-r--r--wqflask/base/data_set/datasetgroup.py193
-rw-r--r--wqflask/base/data_set/datasettype.py122
-rw-r--r--wqflask/base/data_set/genotypedataset.py75
-rw-r--r--wqflask/base/data_set/markers.py96
-rw-r--r--wqflask/base/data_set/mrnaassaydataset.py178
-rw-r--r--wqflask/base/data_set/phenotypedataset.py133
-rw-r--r--wqflask/base/data_set/probably_unused.py34
-rw-r--r--wqflask/base/data_set/tempdataset.py23
-rw-r--r--wqflask/base/data_set/utils.py77
11 files changed, 1347 insertions, 0 deletions
diff --git a/wqflask/base/data_set/__init__.py b/wqflask/base/data_set/__init__.py
new file mode 100644
index 00000000..eaf80b19
--- /dev/null
+++ b/wqflask/base/data_set/__init__.py
@@ -0,0 +1,124 @@
+"The data_set package ..."
+
+# builtins imports
+import json
+import pickle as pickle
+
+# 3rd-party imports
+from redis import Redis
+
+# local imports
+from .dataset import DataSet
+from base import webqtlConfig
+from utility.tools import USE_REDIS
+from .datasettype import DatasetType
+from .tempdataset import TempDataSet
+from .datasetgroup import DatasetGroup
+from .utils import query_table_timestamp
+from .markers import Markers, HumanMarkers
+from .genotypedataset import GenotypeDataSet
+from .phenotypedataset import PhenotypeDataSet
+from .mrnaassaydataset import MrnaAssayDataSet
+from wqflask.database import database_connection
+
+# Used by create_database to instantiate objects
+# Each subclass will add to this
+
+DS_NAME_MAP = {
+ "Temp": "TempDataSet",
+ "Geno": "GenotypeDataSet",
+ "Publish": "PhenotypeDataSet",
+ "ProbeSet": "MrnaAssayDataSet"
+}
+
+# Do the intensive work at startup one time only
+# TODO: Pass in the Redis conniction from elsewhere to allow fo flexible
+# configuration
+Dataset_Getter = DatasetType(Redis())
+
+def create_dataset(dataset_name, dataset_type=None,
+ get_samplelist=True, group_name=None):
+ if dataset_name == "Temp":
+ dataset_type = "Temp"
+
+ if not dataset_type:
+ dataset_type = Dataset_Getter(dataset_name)
+
+ dataset_ob = DS_NAME_MAP[dataset_type]
+ dataset_class = globals()[dataset_ob]
+ if dataset_type == "Temp":
+ return dataset_class(dataset_name, get_samplelist, group_name)
+ else:
+ return dataset_class(dataset_name, get_samplelist)
+
+def datasets(group_name, this_group=None, redis_conn=Redis()):
+ key = "group_dataset_menu:v2:" + group_name
+ dataset_menu = []
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute('''
+ (SELECT '#PublishFreeze',PublishFreeze.FullName,PublishFreeze.Name
+ FROM PublishFreeze,InbredSet
+ WHERE PublishFreeze.InbredSetId = InbredSet.Id
+ and InbredSet.Name = '%s'
+ ORDER BY PublishFreeze.Id ASC)
+ UNION
+ (SELECT '#GenoFreeze',GenoFreeze.FullName,GenoFreeze.Name
+ FROM GenoFreeze, InbredSet
+ WHERE GenoFreeze.InbredSetId = InbredSet.Id
+ and InbredSet.Name = '%s')
+ UNION
+ (SELECT Tissue.Name, ProbeSetFreeze.FullName,ProbeSetFreeze.Name
+ FROM ProbeSetFreeze, ProbeFreeze, InbredSet, Tissue
+ WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id
+ and ProbeFreeze.TissueId = Tissue.Id
+ and ProbeFreeze.InbredSetId = InbredSet.Id
+ and InbredSet.Name like %s
+ ORDER BY Tissue.Name, ProbeSetFreeze.OrderList DESC)
+ ''' % (group_name,
+ group_name,
+ "'" + group_name + "'"))
+ the_results = cursor.fetchall()
+
+ sorted_results = sorted(the_results, key=lambda kv: kv[0])
+
+ # ZS: This is kind of awkward, but need to ensure Phenotypes show up before Genotypes in dropdown
+ pheno_inserted = False
+ geno_inserted = False
+ for dataset_item in sorted_results:
+ tissue_name = dataset_item[0]
+ dataset = dataset_item[1]
+ dataset_short = dataset_item[2]
+ if tissue_name in ['#PublishFreeze', '#GenoFreeze']:
+ if tissue_name == '#PublishFreeze' and (dataset_short == group_name + 'Publish'):
+ dataset_menu.insert(
+ 0, dict(tissue=None, datasets=[(dataset, dataset_short)]))
+ pheno_inserted = True
+ elif pheno_inserted and tissue_name == '#GenoFreeze':
+ dataset_menu.insert(
+ 1, dict(tissue=None, datasets=[(dataset, dataset_short)]))
+ geno_inserted = True
+ else:
+ dataset_menu.append(
+ dict(tissue=None, datasets=[(dataset, dataset_short)]))
+ else:
+ tissue_already_exists = False
+ for i, tissue_dict in enumerate(dataset_menu):
+ if tissue_dict['tissue'] == tissue_name:
+ tissue_already_exists = True
+ break
+
+ if tissue_already_exists:
+ dataset_menu[i]['datasets'].append((dataset, dataset_short))
+ else:
+ dataset_menu.append(dict(tissue=tissue_name,
+ datasets=[(dataset, dataset_short)]))
+
+ if USE_REDIS:
+ redis_conn.set(key, pickle.dumps(dataset_menu, pickle.HIGHEST_PROTOCOL))
+ redis_conn.expire(key, 60 * 5)
+
+ if this_group != None:
+ this_group._datasets = dataset_menu
+ return this_group._datasets
+ else:
+ return dataset_menu
diff --git a/wqflask/base/data_set/dataset.py b/wqflask/base/data_set/dataset.py
new file mode 100644
index 00000000..f035e028
--- /dev/null
+++ b/wqflask/base/data_set/dataset.py
@@ -0,0 +1,292 @@
+"Base Dataset class ..."
+
+import math
+import collections
+
+
+from redis import Redis
+
+
+from base import species
+from utility import chunks
+from .datasetgroup import DatasetGroup
+from wqflask.database import database_connection
+from 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 = None
+
+ 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()
+ if get_samplelist == True:
+ self.group.get_samplelist(redis_conn)
+ self.species = species.TheSpecies(self)
+
+ def as_dict(self):
+ return {
+ 'name': self.name,
+ 'shortname': self.shortname,
+ 'fullname': self.fullname,
+ 'type': self.type,
+ 'data_scale': self.data_scale,
+ 'group': self.group.name,
+ 'accession_id': self.accession_id
+ }
+
+ def get_accession_id(self):
+ results = None
+ with database_connection() as conn, conn.cursor() as cursor:
+ if self.type == "Publish":
+ cursor.execute(
+ "SELECT InfoFiles.GN_AccesionId FROM "
+ "InfoFiles, PublishFreeze, InbredSet "
+ "WHERE InbredSet.Name = %s AND "
+ "PublishFreeze.InbredSetId = InbredSet.Id "
+ "AND InfoFiles.InfoPageName = PublishFreeze.Name "
+ "AND PublishFreeze.public > 0 AND "
+ "PublishFreeze.confidentiality < 1 "
+ "ORDER BY PublishFreeze.CreateTime DESC",
+ (self.group.name,)
+ )
+ results = cursor.fetchone()
+ elif self.type == "Geno":
+ cursor.execute(
+ "SELECT InfoFiles.GN_AccesionId FROM "
+ "InfoFiles, GenoFreeze, InbredSet "
+ "WHERE InbredSet.Name = %s AND "
+ "GenoFreeze.InbredSetId = InbredSet.Id "
+ "AND InfoFiles.InfoPageName = GenoFreeze.ShortName "
+ "AND GenoFreeze.public > 0 AND "
+ "GenoFreeze.confidentiality < 1 "
+ "ORDER BY GenoFreeze.CreateTime DESC",
+ (self.group.name,)
+ )
+ results = cursor.fetchone()
+
+ if results:
+ return str(results[0])
+ return "None"
+
+ 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() 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() 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() 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() 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
diff --git a/wqflask/base/data_set/datasetgroup.py b/wqflask/base/data_set/datasetgroup.py
new file mode 100644
index 00000000..a13d2f93
--- /dev/null
+++ b/wqflask/base/data_set/datasetgroup.py
@@ -0,0 +1,193 @@
+"Dataset Group class ..."
+
+import os
+import json
+
+
+from base import webqtlConfig
+from utility import webqtlUtil
+from utility import gen_geno_ob
+from db import webqtlDatabaseFunction
+from maintenance import get_group_samplelists
+from wqflask.database import database_connection
+from utility.tools import (
+ locate,
+ USE_REDIS,
+ flat_files,
+ flat_file_exists,
+ locate_ignore_error)
+
+class DatasetGroup:
+ """
+ Each group has multiple datasets; each species has multiple groups.
+
+ For example, Mouse has multiple groups (BXD, BXA, etc), and each group
+ has multiple datasets associated with it.
+
+ """
+
+ def __init__(self, dataset, name=None):
+ """This sets self.group and self.group_id"""
+ with database_connection() as conn, conn.cursor() as cursor:
+ if not name:
+ cursor.execute(dataset.query_for_group,
+ (dataset.name,))
+ else:
+ cursor.execute(
+ "SELECT InbredSet.Name, "
+ "InbredSet.Id, "
+ "InbredSet.GeneticType, "
+ "InbredSet.InbredSetCode "
+ "FROM InbredSet WHERE Name = %s",
+ (dataset.name,))
+ results = cursor.fetchone()
+ if results:
+ (self.name, self.id, self.genetic_type, self.code) = results
+ else:
+ self.name = name or dataset.name
+ if self.name == 'BXD300':
+ self.name = "BXD"
+
+ self.f1list = None
+ self.parlist = None
+ self.get_f1_parent_strains()
+
+ self.mapping_id, self.mapping_names = self.get_mapping_methods()
+
+ self.species = webqtlDatabaseFunction.retrieve_species(self.name)
+
+ self.incparentsf1 = False
+ self.allsamples = None
+ self._datasets = None
+ self.genofile = None
+
+ def get_mapping_methods(self):
+ mapping_id = ()
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT MappingMethodId FROM "
+ "InbredSet WHERE Name= %s",
+ (self.name,))
+ results = cursor.fetchone()
+ if results and results[0]:
+ mapping_id = results[0]
+ if mapping_id == "1":
+ mapping_names = ["GEMMA", "QTLReaper", "R/qtl"]
+ elif mapping_id == "2":
+ mapping_names = ["GEMMA"]
+ elif mapping_id == "3":
+ mapping_names = ["R/qtl"]
+ elif mapping_id == "4":
+ mapping_names = ["GEMMA", "PLINK"]
+ else:
+ mapping_names = []
+
+ return mapping_id, mapping_names
+
+ def get_markers(self):
+ def check_plink_gemma():
+ if flat_file_exists("mapping"):
+ MAPPING_PATH = flat_files("mapping") + "/"
+ if os.path.isfile(MAPPING_PATH + self.name + ".bed"):
+ return True
+ return False
+
+ if check_plink_gemma():
+ marker_class = HumanMarkers
+ else:
+ marker_class = Markers
+
+ if self.genofile:
+ self.markers = marker_class(self.genofile[:-5])
+ else:
+ self.markers = marker_class(self.name)
+
+ def get_f1_parent_strains(self):
+ try:
+ # NL, 07/27/2010. ParInfo has been moved from webqtlForm.py to webqtlUtil.py;
+ f1, f12, maternal, paternal = webqtlUtil.ParInfo[self.name]
+ except KeyError:
+ f1 = f12 = maternal = paternal = None
+
+ if f1 and f12:
+ self.f1list = [f1, f12]
+ if maternal and paternal:
+ self.parlist = [maternal, paternal]
+
+ def get_study_samplelists(self):
+ study_sample_file = locate_ignore_error(
+ self.name + ".json", 'study_sample_lists')
+ try:
+ f = open(study_sample_file)
+ except:
+ return []
+ study_samples = json.load(f)
+ return study_samples
+
+ def get_genofiles(self):
+ jsonfile = "%s/%s.json" % (webqtlConfig.GENODIR, self.name)
+ try:
+ f = open(jsonfile)
+ except:
+ return None
+ jsondata = json.load(f)
+ return jsondata['genofile']
+
+ def get_samplelist(self, redis_conn):
+ result = None
+ key = "samplelist:v3:" + self.name
+ if USE_REDIS:
+ result = redis_conn.get(key)
+
+ if result is not None:
+ self.samplelist = json.loads(result)
+ else:
+ genotype_fn = locate_ignore_error(self.name + ".geno", 'genotype')
+ if genotype_fn:
+ self.samplelist = get_group_samplelists.get_samplelist(
+ "geno", genotype_fn)
+ else:
+ self.samplelist = None
+
+ if USE_REDIS:
+ redis_conn.set(key, json.dumps(self.samplelist))
+ redis_conn.expire(key, 60 * 5)
+
+ def all_samples_ordered(self):
+ result = []
+ lists = (self.parlist, self.f1list, self.samplelist)
+ [result.extend(l) for l in lists if l]
+ return result
+
+ def read_genotype_file(self, use_reaper=False):
+ '''Read genotype from .geno file instead of database'''
+ # genotype_1 is Dataset Object without parents and f1
+ # genotype_2 is Dataset Object with parents and f1 (not for intercross)
+
+ # reaper barfs on unicode filenames, so here we ensure it's a string
+ if self.genofile:
+ if "RData" in self.genofile: # ZS: This is a temporary fix; I need to change the way the JSON files that point to multiple genotype files are structured to point to other file types like RData
+ full_filename = str(
+ locate(self.genofile.split(".")[0] + ".geno", 'genotype'))
+ else:
+ full_filename = str(locate(self.genofile, 'genotype'))
+ else:
+ full_filename = str(locate(self.name + '.geno', 'genotype'))
+ genotype_1 = gen_geno_ob.genotype(full_filename)
+
+ if genotype_1.type == "group" and self.parlist:
+ genotype_2 = genotype_1.add(
+ Mat=self.parlist[0], Pat=self.parlist[1]) # , F1=_f1)
+ else:
+ genotype_2 = genotype_1
+
+ # determine default genotype object
+ if self.incparentsf1 and genotype_1.type != "intercross":
+ genotype = genotype_2
+ else:
+ self.incparentsf1 = 0
+ genotype = genotype_1
+
+ self.samplelist = list(genotype.prgy)
+
+ return genotype
diff --git a/wqflask/base/data_set/datasettype.py b/wqflask/base/data_set/datasettype.py
new file mode 100644
index 00000000..ca6515b6
--- /dev/null
+++ b/wqflask/base/data_set/datasettype.py
@@ -0,0 +1,122 @@
+# builtins imports
+
+import json
+import requests
+from dataclasses import field
+from dataclasses import InitVar
+from typing import Optional, Dict
+from dataclasses import dataclass
+
+
+from redis import Redis
+
+
+from utility.tools import GN2_BASE_URL
+from wqflask.database import database_connection
+
+@dataclass
+class DatasetType:
+ """Create a dictionary of samples where the value is set to Geno,
+ Publish or ProbeSet. E.g.
+
+ {'AD-cases-controls-MyersGeno': 'Geno',
+ 'AD-cases-controls-MyersPublish': 'Publish',
+ 'AKXDGeno': 'Geno',
+ 'AXBXAGeno': 'Geno',
+ 'AXBXAPublish': 'Publish',
+ 'Aging-Brain-UCIPublish': 'Publish',
+ 'All Phenotypes': 'Publish',
+ 'B139_K_1206_M': 'ProbeSet',
+ 'B139_K_1206_R': 'ProbeSet' ...
+ }
+ """
+ redis_instance: InitVar[Redis]
+ datasets: Optional[Dict] = field(init=False, default_factory=dict)
+ data: Optional[Dict] = field(init=False)
+
+ def __post_init__(self, redis_instance):
+ self.redis_instance = redis_instance
+ data = redis_instance.get("dataset_structure")
+ if data:
+ self.datasets = json.loads(data)
+ else:
+ # ZS: I don't think this should ever run unless Redis is
+ # emptied
+ try:
+ data = json.loads(requests.get(
+ GN2_BASE_URL + "/api/v_pre1/gen_dropdown",
+ timeout=5).content)
+ for _species in data['datasets']:
+ for group in data['datasets'][_species]:
+ for dataset_type in data['datasets'][_species][group]:
+ for dataset in data['datasets'][_species][group][dataset_type]:
+ short_dataset_name = dataset[1]
+ if dataset_type == "Phenotypes":
+ new_type = "Publish"
+ elif dataset_type == "Genotypes":
+ new_type = "Geno"
+ else:
+ new_type = "ProbeSet"
+ self.datasets[short_dataset_name] = new_type
+ except Exception: # Do nothing
+ pass
+
+ self.redis_instance.set("dataset_structure",
+ json.dumps(self.datasets))
+ self.data = data
+
+ def set_dataset_key(self, t, name):
+ """If name is not in the object's dataset dictionary, set it, and
+ update dataset_structure in Redis
+ args:
+ t: Type of dataset structure which can be: 'mrna_expr', 'pheno',
+ 'other_pheno', 'geno'
+ name: The name of the key to inserted in the datasets dictionary
+
+ """
+ sql_query_mapping = {
+ 'mrna_expr': ("SELECT ProbeSetFreeze.Id FROM "
+ "ProbeSetFreeze WHERE "
+ "ProbeSetFreeze.Name = %s "),
+ 'pheno': ("SELECT InfoFiles.GN_AccesionId "
+ "FROM InfoFiles, PublishFreeze, InbredSet "
+ "WHERE InbredSet.Name = %s AND "
+ "PublishFreeze.InbredSetId = InbredSet.Id AND "
+ "InfoFiles.InfoPageName = PublishFreeze.Name"),
+ 'other_pheno': ("SELECT PublishFreeze.Name "
+ "FROM PublishFreeze, InbredSet "
+ "WHERE InbredSet.Name = %s AND "
+ "PublishFreeze.InbredSetId = InbredSet.Id"),
+ 'geno': ("SELECT GenoFreeze.Id FROM GenoFreeze WHERE "
+ "GenoFreeze.Name = %s ")
+ }
+
+ dataset_name_mapping = {
+ "mrna_expr": "ProbeSet",
+ "pheno": "Publish",
+ "other_pheno": "Publish",
+ "geno": "Geno",
+ }
+
+ group_name = name
+ if t in ['pheno', 'other_pheno']:
+ group_name = name.replace("Publish", "")
+
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute(sql_query_mapping[t], (group_name,))
+ if cursor.fetchone():
+ self.datasets[name] = dataset_name_mapping[t]
+ self.redis_instance.set(
+ "dataset_structure", json.dumps(self.datasets))
+ return True
+
+
+ def __call__(self, name):
+ if name not in self.datasets:
+ for t in ["mrna_expr", "pheno", "other_pheno", "geno"]:
+ # This has side-effects, with the end result being a
+ # truth-y value
+ if(self.set_dataset_key(t, name)):
+ break
+ # Return None if name has not been set
+ return self.datasets.get(name, None)
diff --git a/wqflask/base/data_set/genotypedataset.py b/wqflask/base/data_set/genotypedataset.py
new file mode 100644
index 00000000..2381a42a
--- /dev/null
+++ b/wqflask/base/data_set/genotypedataset.py
@@ -0,0 +1,75 @@
+"GenotypeDataSet class ..."
+
+from .dataset import DataSet
+from utility import webqtlUtil
+from db import webqtlDatabaseFunction
+from .utils import geno_mrna_confidentiality
+from wqflask.database import database_connection
+
+class GenotypeDataSet(DataSet):
+
+ def setup(self):
+ # Fields in the database table
+ self.search_fields = ['Name',
+ 'Chr']
+
+ # Find out what display_fields is
+ self.display_fields = ['name',
+ 'chr',
+ 'mb',
+ 'source2',
+ 'sequence']
+
+ # Fields displayed in the search results table header
+ self.header_fields = ['Index',
+ 'ID',
+ 'Location']
+
+ # Todo: Obsolete or rename this field
+ self.type = 'Geno'
+ self.query_for_group = """
+SELECT InbredSet.Name, InbredSet.Id, InbredSet.GeneticType, InbredSet.InbredSetCode
+FROM InbredSet, GenoFreeze WHERE GenoFreeze.InbredSetId = InbredSet.Id AND
+GenoFreeze.Name = %s"""
+
+ def check_confidentiality(self):
+ return geno_mrna_confidentiality(self)
+
+ def get_trait_info(self, trait_list, species=None):
+ for this_trait in trait_list:
+ if not this_trait.haveinfo:
+ this_trait.retrieveInfo()
+
+ if this_trait.chr and this_trait.mb:
+ this_trait.location_repr = 'Chr%s: %.6f' % (
+ this_trait.chr, float(this_trait.mb))
+
+ def retrieve_sample_data(self, trait):
+ results = []
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT Strain.Name, GenoData.value, "
+ "GenoSE.error, 'N/A', Strain.Name2 "
+ "FROM (GenoData, GenoFreeze, Strain, Geno, "
+ "GenoXRef) LEFT JOIN GenoSE ON "
+ "(GenoSE.DataId = GenoData.Id AND "
+ "GenoSE.StrainId = GenoData.StrainId) "
+ "WHERE Geno.SpeciesId = %s AND "
+ "Geno.Name = %s AND GenoXRef.GenoId = Geno.Id "
+ "AND GenoXRef.GenoFreezeId = GenoFreeze.Id "
+ "AND GenoFreeze.Name = %s AND "
+ "GenoXRef.DataId = GenoData.Id "
+ "AND GenoData.StrainId = Strain.Id "
+ "ORDER BY Strain.Name",
+ (webqtlDatabaseFunction.retrieve_species_id(self.group.name),
+ trait, self.name,))
+ results = list(cursor.fetchall())
+
+ if self.group.name in webqtlUtil.ParInfo:
+ f1_1, f1_2, ref, nonref = webqtlUtil.ParInfo[self.group.name]
+ results.append([f1_1, 0, None, "N/A", f1_1])
+ results.append([f1_2, 0, None, "N/A", f1_2])
+ results.append([ref, -1, None, "N/A", ref])
+ results.append([nonref, 1, None, "N/A", nonref])
+
+ return results
diff --git a/wqflask/base/data_set/markers.py b/wqflask/base/data_set/markers.py
new file mode 100644
index 00000000..6f56445e
--- /dev/null
+++ b/wqflask/base/data_set/markers.py
@@ -0,0 +1,96 @@
+"Base Class: Markers - "
+
+import math
+
+from utility.tools import locate, flat_files
+
+class Markers:
+ """Todo: Build in cacheing so it saves us reading the same file more than once"""
+
+ def __init__(self, name):
+ json_data_fh = open(locate(name + ".json", 'genotype/json'))
+
+ markers = []
+ with open("%s/%s_snps.txt" % (flat_files('genotype/bimbam'), name), 'r') as bimbam_fh:
+ if len(bimbam_fh.readline().split(", ")) > 2:
+ delimiter = ", "
+ elif len(bimbam_fh.readline().split(",")) > 2:
+ delimiter = ","
+ elif len(bimbam_fh.readline().split("\t")) > 2:
+ delimiter = "\t"
+ else:
+ delimiter = " "
+ for line in bimbam_fh:
+ marker = {}
+ marker['name'] = line.split(delimiter)[0].rstrip()
+ marker['Mb'] = float(line.split(delimiter)[
+ 1].rstrip()) / 1000000
+ marker['chr'] = line.split(delimiter)[2].rstrip()
+ markers.append(marker)
+
+ for marker in markers:
+ if (marker['chr'] != "X") and (marker['chr'] != "Y") and (marker['chr'] != "M"):
+ marker['chr'] = int(marker['chr'])
+ marker['Mb'] = float(marker['Mb'])
+
+ self.markers = markers
+
+ def add_pvalues(self, p_values):
+ if isinstance(p_values, list):
+ # THIS IS only needed for the case when we are limiting the number of p-values calculated
+ # if len(self.markers) > len(p_values):
+ # self.markers = self.markers[:len(p_values)]
+
+ for marker, p_value in zip(self.markers, p_values):
+ if not p_value:
+ continue
+ marker['p_value'] = float(p_value)
+ if math.isnan(marker['p_value']) or marker['p_value'] <= 0:
+ marker['lod_score'] = 0
+ marker['lrs_value'] = 0
+ else:
+ marker['lod_score'] = -math.log10(marker['p_value'])
+ # Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values
+ marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61
+ elif isinstance(p_values, dict):
+ filtered_markers = []
+ for marker in self.markers:
+ if marker['name'] in p_values:
+ marker['p_value'] = p_values[marker['name']]
+ if math.isnan(marker['p_value']) or (marker['p_value'] <= 0):
+ marker['lod_score'] = 0
+ marker['lrs_value'] = 0
+ else:
+ marker['lod_score'] = -math.log10(marker['p_value'])
+ # Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values
+ marker['lrs_value'] = - \
+ math.log10(marker['p_value']) * 4.61
+ filtered_markers.append(marker)
+ self.markers = filtered_markers
+
+
+class HumanMarkers(Markers):
+ "Markers for humans ..."
+
+ def __init__(self, name, specified_markers=[]):
+ marker_data_fh = open(flat_files('mapping') + '/' + name + '.bim')
+ self.markers = []
+ for line in marker_data_fh:
+ splat = line.strip().split()
+ if len(specified_markers) > 0:
+ if splat[1] in specified_markers:
+ marker = {}
+ marker['chr'] = int(splat[0])
+ marker['name'] = splat[1]
+ marker['Mb'] = float(splat[3]) / 1000000
+ else:
+ continue
+ else:
+ marker = {}
+ marker['chr'] = int(splat[0])
+ marker['name'] = splat[1]
+ marker['Mb'] = float(splat[3]) / 1000000
+ self.markers.append(marker)
+
+ def add_pvalues(self, p_values):
+ super(HumanMarkers, self).add_pvalues(p_values)
diff --git a/wqflask/base/data_set/mrnaassaydataset.py b/wqflask/base/data_set/mrnaassaydataset.py
new file mode 100644
index 00000000..b76c5a74
--- /dev/null
+++ b/wqflask/base/data_set/mrnaassaydataset.py
@@ -0,0 +1,178 @@
+"MrnaAssayDataSet class ..."
+
+import codecs
+
+
+from .dataset import DataSet
+from .utils import geno_mrna_confidentiality
+from wqflask.database import database_connection
+
+class MrnaAssayDataSet(DataSet):
+ '''
+ An mRNA Assay is a quantitative assessment (assay) associated with an mRNA trait
+
+ This used to be called ProbeSet, but that term only refers specifically to the Affymetrix
+ platform and is far too specific.
+
+ '''
+
+ def setup(self):
+ # Fields in the database table
+ self.search_fields = ['Name',
+ 'Description',
+ 'Probe_Target_Description',
+ 'Symbol',
+ 'Alias',
+ 'GenbankId',
+ 'UniGeneId',
+ 'RefSeq_TranscriptId']
+
+ # Find out what display_fields is
+ self.display_fields = ['name', 'symbol',
+ 'description', 'probe_target_description',
+ 'chr', 'mb',
+ 'alias', 'geneid',
+ 'genbankid', 'unigeneid',
+ 'omim', 'refseq_transcriptid',
+ 'blatseq', 'targetseq',
+ 'chipid', 'comments',
+ 'strand_probe', 'strand_gene',
+ 'proteinid', 'uniprotid',
+ 'probe_set_target_region',
+ 'probe_set_specificity',
+ 'probe_set_blat_score',
+ 'probe_set_blat_mb_start',
+ 'probe_set_blat_mb_end',
+ 'probe_set_strand',
+ 'probe_set_note_by_rw',
+ 'flag']
+
+ # Fields displayed in the search results table header
+ self.header_fields = ['Index',
+ 'Record',
+ 'Symbol',
+ 'Description',
+ 'Location',
+ 'Mean',
+ 'Max LRS',
+ 'Max LRS Location',
+ 'Additive Effect']
+
+ # Todo: Obsolete or rename this field
+ self.type = 'ProbeSet'
+ self.query_for_group = """
+SELECT InbredSet.Name, InbredSet.Id, InbredSet.GeneticType, InbredSet.InbredSetCode
+FROM InbredSet, ProbeSetFreeze, ProbeFreeze WHERE ProbeFreeze.InbredSetId = InbredSet.Id AND
+ProbeFreeze.Id = ProbeSetFreeze.ProbeFreezeId AND ProbeSetFreeze.Name = %s"""
+
+ def check_confidentiality(self):
+ return geno_mrna_confidentiality(self)
+
+ def get_trait_info(self, trait_list=None, species=''):
+
+ # Note: setting trait_list to [] is probably not a great idea.
+ if not trait_list:
+ trait_list = []
+ with database_connection() as conn, conn.cursor() as cursor:
+ for this_trait in trait_list:
+
+ if not this_trait.haveinfo:
+ this_trait.retrieveInfo(QTL=1)
+
+ if not this_trait.symbol:
+ this_trait.symbol = "N/A"
+
+ # XZ, 12/08/2008: description
+ # XZ, 06/05/2009: Rob asked to add probe target description
+ description_string = str(
+ str(this_trait.description).strip(codecs.BOM_UTF8), 'utf-8')
+ target_string = str(
+ str(this_trait.probe_target_description).strip(codecs.BOM_UTF8), 'utf-8')
+
+ if len(description_string) > 1 and description_string != 'None':
+ description_display = description_string
+ else:
+ description_display = this_trait.symbol
+
+ if (len(description_display) > 1 and description_display != 'N/A'
+ and len(target_string) > 1 and target_string != 'None'):
+ description_display = description_display + '; ' + target_string.strip()
+
+ # Save it for the jinja2 template
+ this_trait.description_display = description_display
+
+ if this_trait.chr and this_trait.mb:
+ this_trait.location_repr = 'Chr%s: %.6f' % (
+ this_trait.chr, float(this_trait.mb))
+
+ # Get mean expression value
+ cursor.execute(
+ "SELECT ProbeSetXRef.mean FROM "
+ "ProbeSetXRef, ProbeSet WHERE "
+ "ProbeSetXRef.ProbeSetFreezeId = %s "
+ "AND ProbeSet.Id = ProbeSetXRef.ProbeSetId "
+ "AND ProbeSet.Name = %s",
+ (str(this_trait.dataset.id), this_trait.name,)
+ )
+ result = cursor.fetchone()
+
+ mean = result[0] if result else 0
+
+ if mean:
+ this_trait.mean = "%2.3f" % mean
+
+ # LRS and its location
+ this_trait.LRS_score_repr = 'N/A'
+ this_trait.LRS_location_repr = 'N/A'
+
+ # Max LRS and its Locus location
+ if this_trait.lrs and this_trait.locus:
+ cursor.execute(
+ "SELECT Geno.Chr, Geno.Mb FROM "
+ "Geno, Species WHERE "
+ "Species.Name = %s AND "
+ "Geno.Name = %s AND "
+ "Geno.SpeciesId = Species.Id",
+ (species, this_trait.locus,)
+ )
+ if result := cursor.fetchone():
+ lrs_chr, lrs_mb = result
+ this_trait.LRS_score_repr = '%3.1f' % this_trait.lrs
+ this_trait.LRS_location_repr = 'Chr%s: %.6f' % (
+ lrs_chr, float(lrs_mb))
+
+ return trait_list
+
+ def retrieve_sample_data(self, trait):
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT Strain.Name, ProbeSetData.value, "
+ "ProbeSetSE.error, NStrain.count, "
+ "Strain.Name2 FROM (ProbeSetData, "
+ "ProbeSetFreeze, Strain, ProbeSet, "
+ "ProbeSetXRef) LEFT JOIN ProbeSetSE ON "
+ "(ProbeSetSE.DataId = ProbeSetData.Id AND "
+ "ProbeSetSE.StrainId = ProbeSetData.StrainId) "
+ "LEFT JOIN NStrain ON "
+ "(NStrain.DataId = ProbeSetData.Id AND "
+ "NStrain.StrainId = ProbeSetData.StrainId) "
+ "WHERE ProbeSet.Name = %s AND "
+ "ProbeSetXRef.ProbeSetId = ProbeSet.Id "
+ "AND ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id "
+ "AND ProbeSetFreeze.Name = %s AND "
+ "ProbeSetXRef.DataId = ProbeSetData.Id "
+ "AND ProbeSetData.StrainId = Strain.Id "
+ "ORDER BY Strain.Name",
+ (trait, self.name,)
+ )
+ return cursor.fetchall()
+
+ def retrieve_genes(self, column_name):
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute(
+ f"SELECT ProbeSet.Name, ProbeSet.{column_name} "
+ "FROM ProbeSet,ProbeSetXRef WHERE "
+ "ProbeSetXRef.ProbeSetFreezeId = %s "
+ "AND ProbeSetXRef.ProbeSetId=ProbeSet.Id",
+ (str(self.id),))
+ return dict(cursor.fetchall())
diff --git a/wqflask/base/data_set/phenotypedataset.py b/wqflask/base/data_set/phenotypedataset.py
new file mode 100644
index 00000000..bdf28a7a
--- /dev/null
+++ b/wqflask/base/data_set/phenotypedataset.py
@@ -0,0 +1,133 @@
+"PhenotypeDataSet class ..."
+
+from .dataset import DataSet
+from base import webqtlConfig
+from wqflask.database import database_connection
+
+class PhenotypeDataSet(DataSet):
+
+ def setup(self):
+ # Fields in the database table
+ self.search_fields = ['Phenotype.Post_publication_description',
+ 'Phenotype.Pre_publication_description',
+ 'Phenotype.Pre_publication_abbreviation',
+ 'Phenotype.Post_publication_abbreviation',
+ 'PublishXRef.mean',
+ 'Phenotype.Lab_code',
+ 'Publication.PubMed_ID',
+ 'Publication.Abstract',
+ 'Publication.Title',
+ 'Publication.Authors',
+ 'PublishXRef.Id']
+
+ # Figure out what display_fields is
+ self.display_fields = ['name', 'group_code',
+ 'pubmed_id',
+ 'pre_publication_description',
+ 'post_publication_description',
+ 'original_description',
+ 'pre_publication_abbreviation',
+ 'post_publication_abbreviation',
+ 'mean',
+ 'lab_code',
+ 'submitter', 'owner',
+ 'authorized_users',
+ 'authors', 'title',
+ 'abstract', 'journal',
+ 'volume', 'pages',
+ 'month', 'year',
+ 'sequence', 'units', 'comments']
+
+ # Fields displayed in the search results table header
+ self.header_fields = ['Index',
+ 'Record',
+ 'Description',
+ 'Authors',
+ 'Year',
+ 'Max LRS',
+ 'Max LRS Location',
+ 'Additive Effect']
+
+ self.type = 'Publish'
+ self.query_for_group = """
+SELECT InbredSet.Name, InbredSet.Id, InbredSet.GeneticType, InbredSet.InbredSetCode FROM InbredSet, PublishFreeze WHERE PublishFreeze.InbredSetId = InbredSet.Id AND PublishFreeze.Name = %s"""
+
+ def check_confidentiality(self):
+ # (Urgently?) Need to write this
+ pass
+
+ def get_trait_info(self, trait_list, species=''):
+ for this_trait in trait_list:
+
+ if not this_trait.haveinfo:
+ this_trait.retrieve_info(get_qtl_info=True)
+
+ description = this_trait.post_publication_description
+
+ # If the dataset is confidential and the user has access to confidential
+ # phenotype traits, then display the pre-publication description instead
+ # of the post-publication description
+ if this_trait.confidential:
+ this_trait.description_display = ""
+ continue # for now, because no authorization features
+
+ if not webqtlUtil.hasAccessToConfidentialPhenotypeTrait(
+ privilege=self.privilege,
+ userName=self.userName,
+ authorized_users=this_trait.authorized_users):
+
+ description = this_trait.pre_publication_description
+
+ if len(description) > 0:
+ this_trait.description_display = description.strip()
+ else:
+ this_trait.description_display = ""
+
+ if not this_trait.year.isdigit():
+ this_trait.pubmed_text = "N/A"
+ else:
+ this_trait.pubmed_text = this_trait.year
+
+ if this_trait.pubmed_id:
+ this_trait.pubmed_link = webqtlConfig.PUBMEDLINK_URL % this_trait.pubmed_id
+
+ # LRS and its location
+ this_trait.LRS_score_repr = "N/A"
+ this_trait.LRS_location_repr = "N/A"
+
+ if this_trait.lrs:
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT Geno.Chr, Geno.Mb FROM "
+ "Geno, Species WHERE "
+ "Species.Name = %s AND "
+ "Geno.Name = %s AND "
+ "Geno.SpeciesId = Species.Id",
+ (species, this_trait.locus,)
+ )
+ if result := cursor.fetchone():
+ if result[0] and result[1]:
+ LRS_Chr, LRS_Mb = result[0], result[1]
+ this_trait.LRS_score_repr = LRS_score_repr = '%3.1f' % this_trait.lrs
+ this_trait.LRS_location_repr = LRS_location_repr = 'Chr%s: %.6f' % (
+ LRS_Chr, float(LRS_Mb))
+
+ def retrieve_sample_data(self, trait):
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT Strain.Name, PublishData.value, "
+ "PublishSE.error, NStrain.count, "
+ "Strain.Name2 FROM (PublishData, Strain, "
+ "PublishXRef, PublishFreeze) LEFT JOIN "
+ "PublishSE ON "
+ "(PublishSE.DataId = PublishData.Id "
+ "AND PublishSE.StrainId = PublishData.StrainId) "
+ "LEFT JOIN NStrain ON "
+ "(NStrain.DataId = PublishData.Id AND "
+ "NStrain.StrainId = PublishData.StrainId) "
+ "WHERE PublishXRef.InbredSetId = PublishFreeze.InbredSetId "
+ "AND PublishData.Id = PublishXRef.DataId AND "
+ "PublishXRef.Id = %s AND PublishFreeze.Id = %s "
+ "AND PublishData.StrainId = Strain.Id "
+ "ORDER BY Strain.Name", (trait, self.id))
+ return cursor.fetchall()
diff --git a/wqflask/base/data_set/probably_unused.py b/wqflask/base/data_set/probably_unused.py
new file mode 100644
index 00000000..4e54bcff
--- /dev/null
+++ b/wqflask/base/data_set/probably_unused.py
@@ -0,0 +1,34 @@
+"Functions that are probably unused in the code"
+
+import pickle as pickle
+
+from wqflask.database import database_connection
+
+def create_datasets_list():
+ if USE_REDIS:
+ key = "all_datasets"
+ result = redis_conn.get(key)
+
+ if result:
+ datasets = pickle.loads(result)
+
+ if result is None:
+ datasets = list()
+ type_dict = {'Publish': 'PublishFreeze',
+ 'ProbeSet': 'ProbeSetFreeze',
+ 'Geno': 'GenoFreeze'}
+
+ for dataset_type in type_dict:
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute("SELECT Name FROM %s",
+ (type_dict[dataset_type],))
+ results = cursor.fetchall(query)
+ if results:
+ for result in results:
+ datasets.append(
+ create_dataset(result.Name, dataset_type))
+ if USE_REDIS:
+ redis_conn.set(key, pickle.dumps(datasets, pickle.HIGHEST_PROTOCOL))
+ redis_conn.expire(key, 60 * 60)
+
+ return datasets
diff --git a/wqflask/base/data_set/tempdataset.py b/wqflask/base/data_set/tempdataset.py
new file mode 100644
index 00000000..b1c26a3b
--- /dev/null
+++ b/wqflask/base/data_set/tempdataset.py
@@ -0,0 +1,23 @@
+"TempDataSet class ..."
+
+from .dataset import DataSet
+
+class TempDataSet(DataSet):
+ """Temporary user-generated data set"""
+
+ def setup(self):
+ self.search_fields = ['name',
+ 'description']
+
+ self.display_fields = ['name',
+ 'description']
+
+ self.header_fields = ['Name',
+ 'Description']
+
+ self.type = 'Temp'
+
+ # Need to double check later how these are used
+ self.id = 1
+ self.fullname = 'Temporary Storage'
+ self.shortname = 'Temp'
diff --git a/wqflask/base/data_set/utils.py b/wqflask/base/data_set/utils.py
new file mode 100644
index 00000000..0077c292
--- /dev/null
+++ b/wqflask/base/data_set/utils.py
@@ -0,0 +1,77 @@
+"data_set package utilities"
+
+import os
+import json
+import hashlib
+from typing import List
+
+
+from utility.tools import SQL_URI
+from base.webqtlConfig import TMPDIR
+from wqflask.database import parse_db_url, database_connection
+
+def geno_mrna_confidentiality(ob):
+ with database_connection() as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT confidentiality, "
+ f"AuthorisedUsers FROM {ob.type}Freeze WHERE Name = %s",
+ (ob.name,)
+ )
+ result = cursor.fetchall()
+ if len(result) > 0 and result[0]:
+ return True
+
+def query_table_timestamp(dataset_type: str):
+ """function to query the update timestamp of a given dataset_type"""
+
+ # computation data and actions
+ with database_connection() as conn, conn.cursor() as cursor:
+ fetch_db_name = parse_db_url(SQL_URI)
+ cursor.execute(
+ "SELECT UPDATE_TIME FROM "
+ "information_schema.tables "
+ f"WHERE TABLE_SCHEMA = '{fetch_db_name[3]}' "
+ f"AND TABLE_NAME = '{dataset_type}Data'")
+ date_time_obj = cursor.fetchone()[0]
+ return date_time_obj.strftime("%Y-%m-%d %H:%M:%S")
+
+
+def generate_hash_file(dataset_name: str, dataset_type: str, dataset_timestamp: str, samplelist: str):
+ """given the trait_name generate a unique name for this"""
+ string_unicode = f"{dataset_name}{dataset_timestamp}{samplelist}".encode()
+ md5hash = hashlib.md5(string_unicode)
+ return md5hash.hexdigest()
+
+
+def cache_dataset_results(dataset_name: str, dataset_type: str, samplelist: List, query_results: List):
+ """function to cache dataset query results to file
+ input dataset_name and type query_results(already processed in default dict format)
+ """
+ # data computations actions
+ # store the file path on redis
+
+ table_timestamp = query_table_timestamp(dataset_type)
+ samplelist_as_str = ",".join(samplelist)
+
+ file_name = generate_hash_file(dataset_name, dataset_type, table_timestamp, samplelist_as_str)
+ file_path = os.path.join(TMPDIR, f"{file_name}.json")
+
+ with open(file_path, "w") as file_handler:
+ json.dump(query_results, file_handler)
+
+
+def fetch_cached_results(dataset_name: str, dataset_type: str, samplelist: List):
+ """function to fetch the cached results"""
+
+ table_timestamp = query_table_timestamp(dataset_type)
+ samplelist_as_str = ",".join(samplelist)
+
+ file_name = generate_hash_file(dataset_name, dataset_type, table_timestamp, samplelist_as_str)
+ file_path = os.path.join(TMPDIR, f"{file_name}.json")
+ try:
+ with open(file_path, "r") as file_handler:
+
+ return json.load(file_handler)
+
+ except Exception:
+ pass
generated by cgit v1.2.3 (git 2.44.0) at 2024-11-22 21:08:01 +0000