Decompose file into separate modulesrefactor-data_set_py-20220920

To ease future refactors on the code, decompose the file into a module
with multiple modules that can be refactored semi-independently.

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