# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
#
# This program is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License
# as published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
# See the GNU Affero General Public License for more details.
#
# This program is available from Source Forge: at GeneNetwork Project
# (sourceforge.net/projects/genenetwork/).
#
# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
#
# This module is used by GeneNetwork project (www.genenetwork.org)
from __future__ import absolute_import, print_function, division
import os
import math
import string
import collections
import codecs
import json
import requests
import gzip
import cPickle as pickle
import itertools
from redis import Redis
Redis = Redis()
from flask import Flask, g
import reaper
from base import webqtlConfig
from base import species
from db import webqtlDatabaseFunction
from utility import webqtlUtil
from utility.benchmark import Bench
from utility import chunks
from utility import gen_geno_ob
from utility.tools import locate, locate_ignore_error, flat_files
from wqflask.api import gen_menu
from maintenance import get_group_samplelists
from MySQLdb import escape_string as escape
from pprint import pformat as pf
from db.gn_server import menu_main
from db.call import fetchall,fetchone,fetch1
from utility.tools import USE_GN_SERVER, USE_REDIS, flat_files, flat_file_exists
from utility.logger import getLogger
logger = getLogger(__name__ )
# Used by create_database to instantiate objects
# Each subclass will add to this
DS_NAME_MAP = {}
def create_dataset(dataset_name, rebuild=True, dataset_type = None, get_samplelist = True, group_name = None):
if not dataset_type:
dataset_type = Dataset_Getter(dataset_name)
logger.debug("dataset_type", dataset_type)
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)
class Dataset_Types(object):
def __init__(self, rebuild=False):
"""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' ...
"""
self.datasets = {}
if rebuild: #ZS: May make this the only option
data = json.loads(requests.get("http://gn2.genenetwork.org/api/v_pre1/gen_dropdown").content)
logger.debug("THE DATA:", data)
#data = gen_menu.gen_dropdown_json()
else:
file_name = "wqflask/static/new/javascript/dataset_menu_structure.json"
with open(file_name, 'r') as fh:
data = json.load(fh)
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
# Set LOG_LEVEL_DEBUG=5 to see the following:
logger.debugf(5, "datasets",self.datasets)
def __call__(self, name):
return self.datasets[name]
# Do the intensive work at startup one time only
Dataset_Getter = Dataset_Types()
def create_datasets_list():
if USE_REDIS:
key = "all_datasets"
result = Redis.get(key)
if result:
logger.debug("Redis cache hit")
datasets = pickle.loads(result)
if result is None:
datasets = list()
with Bench("Creating DataSets object"):
type_dict = {'Publish': 'PublishFreeze',
'ProbeSet': 'ProbeSetFreeze',
'Geno': 'GenoFreeze'}
for dataset_type in type_dict:
query = "SELECT Name FROM {}".format(type_dict[dataset_type])
for result in fetchall(query):
#The query at the beginning of this function isn't
#necessary here, but still would rather just reuse
#it logger.debug("type: {}\tname:
#{}".format(dataset_type, result.Name))
dataset = create_dataset(result.Name, dataset_type)
datasets.append(dataset)
if USE_REDIS:
Redis.set(key, pickle.dumps(datasets, pickle.HIGHEST_PROTOCOL))
Redis.expire(key, 60*60)
return datasets
def create_in_clause(items):
"""Create an in clause for mysql"""
in_clause = ', '.join("'{}'".format(x) for x in mescape(*items))
in_clause = '( {} )'.format(in_clause)
return in_clause
def mescape(*items):
"""Multiple escape"""
escaped = [escape(str(item)) for item in items]
#logger.debug("escaped is:", escaped)
return escaped
class Markers(object):
"""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):
logger.debug("length of self.markers:", len(self.markers))
logger.debug("length of p_values:", len(p_values))
if type(p_values) is 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 itertools.izip(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 type(p_values) is dict:
filtered_markers = []
for marker in self.markers:
#logger.debug("marker[name]", marker['name'])
#logger.debug("p_values:", p_values)
if marker['name'] in p_values:
#logger.debug("marker {} IS in p_values".format(i))
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)
#else:
#logger.debug("marker {} NOT in p_values".format(i))
#self.markers.remove(marker)
#del self.markers[i]
self.markers = filtered_markers
class HumanMarkers(Markers):
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()
#logger.debug("splat:", splat)
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)
#logger.debug("markers is: ", pf(self.markers))
def add_pvalues(self, p_values):
super(HumanMarkers, self).add_pvalues(p_values)
class DatasetGroup(object):
"""
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"""
if name == None:
self.name, self.id, self.genetic_type = fetchone(dataset.query_for_group)
else:
self.name, self.id, self.genetic_type = fetchone("SELECT InbredSet.Name, InbredSet.Id, InbredSet.GeneticType FROM InbredSet where Name='%s'" % 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 = g.db.execute("select MappingMethodId from InbredSet where Name= '%s'" % self.name).fetchone()[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_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):
result = None
key = "samplelist:v3:" + self.name
if USE_REDIS:
result = Redis.get(key)
if result is not None:
self.samplelist = json.loads(result)
else:
logger.debug("Cache not hit")
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.set(key, json.dumps(self.samplelist))
Redis.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)
#genotype_1 = reaper.Dataset()
# 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'))
if use_reaper:
genotype_1 = reaper.Dataset()
genotype_1.read(full_filename)
else:
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
def datasets(group_name, this_group = None):
key = "group_dataset_menu:v2:" + group_name
logger.debug("key is2:", key)
dataset_menu = []
logger.debug("[tape4] webqtlConfig.PUBLICTHRESH:", webqtlConfig.PUBLICTHRESH)
logger.debug("[tape4] type webqtlConfig.PUBLICTHRESH:", type(webqtlConfig.PUBLICTHRESH))
the_results = fetchall('''
(SELECT '#PublishFreeze',PublishFreeze.FullName,PublishFreeze.Name
FROM PublishFreeze,InbredSet
WHERE PublishFreeze.InbredSetId = InbredSet.Id
and InbredSet.Name = '%s'
and PublishFreeze.public > %s
and PublishFreeze.confidentiality < 1
ORDER BY PublishFreeze.Id ASC)
UNION
(SELECT '#GenoFreeze',GenoFreeze.FullName,GenoFreeze.Name
FROM GenoFreeze, InbredSet
WHERE GenoFreeze.InbredSetId = InbredSet.Id
and InbredSet.Name = '%s'
and GenoFreeze.public > %s
and GenoFreeze.confidentiality < 1)
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
and ProbeSetFreeze.public > %s
and ProbeSetFreeze.confidentiality < 1
ORDER BY Tissue.Name, ProbeSetFreeze.OrderList DESC)
''' % (group_name, webqtlConfig.PUBLICTHRESH,
group_name, webqtlConfig.PUBLICTHRESH,
"'" + group_name + "'", webqtlConfig.PUBLICTHRESH))
sorted_results = sorted(the_results, key=lambda kv: kv[0])
pheno_inserted = False #ZS: This is kind of awkward, but need to ensure Phenotypes show up before Genotypes in dropdown
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:
#logger.debug("dataset_menu:", dataset_menu[i]['datasets'])
dataset_menu[i]['datasets'].append((dataset, dataset_short))
else:
dataset_menu.append(dict(tissue=tissue_name,
datasets=[(dataset, dataset_short)]))
if USE_REDIS:
Redis.set(key, pickle.dumps(dataset_menu, pickle.HIGHEST_PROTOCOL))
Redis.expire(key, 60*5)
if this_group != None:
this_group._datasets = dataset_menu
return this_group._datasets
else:
return dataset_menu
class DataSet(object):
"""
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):
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.setup()
if self.type == "Temp": #Need to supply group name as input if temp trait
self.group = DatasetGroup(self, name=group_name) # sets self.group and self.group_id and gets genotype
else:
self.check_confidentiality()
self.retrieve_other_names()
self.group = DatasetGroup(self) # sets self.group and self.group_id and gets genotype
self.accession_id = self.get_accession_id()
if get_samplelist == True:
self.group.get_samplelist()
self.species = species.TheSpecies(self)
def get_desc(self):
"""Gets overridden later, at least for Temp...used by trait's get_given_name"""
return None
# Delete this eventually
@property
def riset():
Weve_Renamed_This_As_Group
def get_accession_id(self):
if self.type == "Publish":
results = g.db.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)).fetchone()
elif self.type == "Geno":
results = g.db.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)).fetchone()
else:
results = None
if results != None:
return str(results[0])
else:
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.
"""
try:
if self.type == "ProbeSet":
query_args = tuple(escape(x) for x in (
str(webqtlConfig.PUBLICTHRESH),
self.name,
self.name,
self.name))
self.id, self.name, self.fullname, self.shortname, self.data_scale, self.tissue = fetch1("""
SELECT ProbeSetFreeze.Id, ProbeSetFreeze.Name, ProbeSetFreeze.FullName, ProbeSetFreeze.ShortName, ProbeSetFreeze.DataScale, Tissue.Name
FROM ProbeSetFreeze, ProbeFreeze, Tissue
WHERE ProbeSetFreeze.public > %s
AND ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id
AND ProbeFreeze.TissueId = Tissue.Id
AND (ProbeSetFreeze.Name = '%s' OR ProbeSetFreeze.FullName = '%s' OR ProbeSetFreeze.ShortName = '%s')
""" % (query_args),"/dataset/"+self.name+".json",
lambda r: (r["id"],r["name"],r["full_name"],r["short_name"],r["data_scale"],r["tissue"])
)
else:
query_args = tuple(escape(x) for x in (
(self.type + "Freeze"),
str(webqtlConfig.PUBLICTHRESH),
self.name,
self.name,
self.name))
self.tissue = "N/A"
self.id, self.name, self.fullname, self.shortname = fetchone("""
SELECT Id, Name, FullName, ShortName
FROM %s
WHERE public > %s AND
(Name = '%s' OR FullName = '%s' OR ShortName = '%s')
""" % (query_args))
except TypeError:
logger.debug("Dataset {} is not yet available in GeneNetwork.".format(self.name))
pass
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
query = """
SELECT Strain.Name, Strain.Id FROM Strain, Species
WHERE Strain.Name IN {}
and Strain.SpeciesId=Species.Id
and Species.name = '{}'
""".format(create_in_clause(self.samplelist), *mescape(self.group.species))
logger.sql(query)
results = dict(g.db.execute(query).fetchall())
sample_ids = [results[item] for item in self.samplelist]
# 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))
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
query += string.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))
#logger.debug("trait data query: ", query)
logger.sql(query)
results = g.db.execute(query).fetchall()
#logger.debug("query results:", results)
trait_sample_data.append(results)
trait_count = len(trait_sample_data[0])
self.trait_data = collections.defaultdict(list)
# put all of the separate data together into a dictionary where the keys are
# trait names and values are lists of sample values
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:])
class PhenotypeDataSet(DataSet):
DS_NAME_MAP['Publish'] = 'PhenotypeDataSet'
def setup(self):
#logger.debug("IS A PHENOTYPEDATASET")
# 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
FROM
InbredSet, PublishFreeze
WHERE
PublishFreeze.InbredSetId = InbredSet.Id AND
PublishFreeze.Name = "%s"
''' % escape(self.name)
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:
query = """
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)
logger.sql(query)
result = g.db.execute(query).fetchone()
if result:
if result[0] and result[1]:
LRS_Chr = result[0]
LRS_Mb = 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):
query = """
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
"""
logger.sql(query)
results = g.db.execute(query, (trait, self.id)).fetchall()
return results
class GenotypeDataSet(DataSet):
DS_NAME_MAP['Geno'] = 'GenotypeDataSet'
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
FROM
InbredSet, GenoFreeze
WHERE
GenoFreeze.InbredSetId = InbredSet.Id AND
GenoFreeze.Name = "%s"
''' % escape(self.name)
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):
query = """
SELECT
Strain.Name, GenoData.value, GenoSE.error, GenoData.Id, 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
"""
logger.sql(query)
results = g.db.execute(query,
(webqtlDatabaseFunction.retrieve_species_id(self.group.name),
trait, self.name)).fetchall()
return results
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.
'''
DS_NAME_MAP['ProbeSet'] = 'MrnaAssayDataSet'
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
FROM
InbredSet, ProbeSetFreeze, ProbeFreeze
WHERE
ProbeFreeze.InbredSetId = InbredSet.Id AND
ProbeFreeze.Id = ProbeSetFreeze.ProbeFreezeId AND
ProbeSetFreeze.Name = "%s"
''' % escape(self.name)
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 = []
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 = unicode(str(this_trait.description).strip(codecs.BOM_UTF8), 'utf-8')
target_string = unicode(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
query = (
"""select ProbeSetXRef.mean from ProbeSetXRef, ProbeSet
where ProbeSetXRef.ProbeSetFreezeId = %s and
ProbeSet.Id = ProbeSetXRef.ProbeSetId and
ProbeSet.Name = '%s'
""" % (escape(str(this_trait.dataset.id)),
escape(this_trait.name)))
#logger.debug("query is:", pf(query))
logger.sql(query)
result = g.db.execute(query).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:
query = """
select Geno.Chr, Geno.Mb from Geno, Species
where Species.Name = '{}' and
Geno.Name = '{}' and
Geno.SpeciesId = Species.Id
""".format(species, this_trait.locus)
logger.sql(query)
result = g.db.execute(query).fetchone()
if result:
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):
query = """
SELECT
Strain.Name, ProbeSetData.value, ProbeSetSE.error, ProbeSetData.Id, Strain.Name2
FROM
(ProbeSetData, ProbeSetFreeze, Strain, ProbeSet, ProbeSetXRef)
left join ProbeSetSE on
(ProbeSetSE.DataId = ProbeSetData.Id AND ProbeSetSE.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
""" % (escape(trait), escape(self.name))
logger.sql(query)
results = g.db.execute(query).fetchall()
#logger.debug("RETRIEVED RESULTS HERE:", results)
return results
def retrieve_genes(self, column_name):
query = """
select ProbeSet.Name, ProbeSet.%s
from ProbeSet,ProbeSetXRef
where ProbeSetXRef.ProbeSetFreezeId = %s and
ProbeSetXRef.ProbeSetId=ProbeSet.Id;
""" % (column_name, escape(str(self.id)))
logger.sql(query)
results = g.db.execute(query).fetchall()
return dict(results)
class TempDataSet(DataSet):
'''Temporary user-generated data set'''
DS_NAME_MAP['Temp'] = 'TempDataSet'
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'
@staticmethod
def handle_pca(desc):
if 'PCA' in desc:
# Todo: Modernize below lines
desc = desc[desc.rindex(':')+1:].strip()
else:
desc = desc[:desc.index('entered')].strip()
return desc
def get_desc(self):
query = 'SELECT description FROM Temp WHERE Name=%s' % self.name
logger.sql(query)
g.db.execute(query)
desc = g.db.fetchone()[0]
desc = self.handle_pca(desc)
return desc
def retrieve_sample_data(self, trait):
query = """
SELECT
Strain.Name, TempData.value, TempData.SE, TempData.NStrain, TempData.Id
FROM
TempData, Temp, Strain
WHERE
TempData.StrainId = Strain.Id AND
TempData.Id = Temp.DataId AND
Temp.name = '%s'
Order BY
Strain.Name
""" % escape(trait.name)
logger.sql(query)
results = g.db.execute(query).fetchall()
def geno_mrna_confidentiality(ob):
dataset_table = ob.type + "Freeze"
#logger.debug("dataset_table [%s]: %s" % (type(dataset_table), dataset_table))
query = '''SELECT Id, Name, FullName, confidentiality,
AuthorisedUsers FROM %s WHERE Name = "%s"''' % (dataset_table,ob.name)
logger.sql(query)
result = g.db.execute(query)
(dataset_id,
name,
full_name,
confidential,
authorized_users) = result.fetchall()[0]
if confidential:
return True
