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authorBonfaceKilz2021-04-29 15:36:24 +0300
committerBonfaceKilz2021-04-29 15:36:24 +0300
commite3593f24b18c085c88e783addf3f7eb990341efc (patch)
tree334b032569409474c02643812d42f00754f27445 /wqflask
parent3197cb6fffffa437e91f936457c29c498a9f4ec8 (diff)
downloadgenenetwork2-e3593f24b18c085c88e783addf3f7eb990341efc.tar.gz
wqflask: show_trait: Autopep-8 buffer
Diffstat (limited to 'wqflask')
-rw-r--r--wqflask/wqflask/show_trait/show_trait.py237
1 files changed, 139 insertions, 98 deletions
diff --git a/wqflask/wqflask/show_trait/show_trait.py b/wqflask/wqflask/show_trait/show_trait.py
index 457eb902..e5e94c7e 100644
--- a/wqflask/wqflask/show_trait/show_trait.py
+++ b/wqflask/wqflask/show_trait/show_trait.py
@@ -19,20 +19,22 @@ from utility import helper_functions
from utility.authentication_tools import check_owner_or_admin
from utility.tools import locate_ignore_error
from utility.redis_tools import get_redis_conn, get_resource_id
+from utility.logger import getLogger
+
+
Redis = get_redis_conn()
ONE_YEAR = 60 * 60 * 24 * 365
-
-from utility.logger import getLogger
-logger = getLogger(__name__ )
+logger = getLogger(__name__)
###############################################
#
-# Todo: Put in security to ensure that user has permission to access confidential data sets
-# And add i.p.limiting as necessary
+# Todo: Put in security to ensure that user has permission to access
+# confidential data sets And add i.p.limiting as necessary
#
##############################################
+
class ShowTrait(object):
def __init__(self, kw):
@@ -41,13 +43,16 @@ class ShowTrait(object):
self.trait_id = kw['trait_id']
helper_functions.get_species_dataset_trait(self, kw)
self.resource_id = get_resource_id(self.dataset, self.trait_id)
- self.admin_status = check_owner_or_admin(resource_id=self.resource_id)
+ self.admin_status = check_owner_or_admin(
+ resource_id=self.resource_id)
elif 'group' in kw:
self.temp_trait = True
- self.trait_id = "Temp_"+kw['species']+ "_" + kw['group'] + "_" + datetime.datetime.now().strftime("%m%d%H%M%S")
+ self.trait_id = "Temp_"+kw['species'] + "_" + kw['group'] + \
+ "_" + datetime.datetime.now().strftime("%m%d%H%M%S")
self.temp_species = kw['species']
self.temp_group = kw['group']
- self.dataset = data_set.create_dataset(dataset_name = "Temp", dataset_type = "Temp", group_name = self.temp_group)
+ self.dataset = data_set.create_dataset(
+ dataset_name="Temp", dataset_type="Temp", group_name=self.temp_group)
# Put values in Redis so they can be looked up later if added to a collection
Redis.set(self.trait_id, kw['trait_paste'], ex=ONE_YEAR)
@@ -56,25 +61,28 @@ class ShowTrait(object):
name=self.trait_id,
cellid=None)
- self.admin_status = check_owner_or_admin(dataset=self.dataset, trait_id=self.trait_id)
+ self.admin_status = check_owner_or_admin(
+ dataset=self.dataset, trait_id=self.trait_id)
else:
self.temp_trait = True
self.trait_id = kw['trait_id']
self.temp_species = self.trait_id.split("_")[1]
self.temp_group = self.trait_id.split("_")[2]
- self.dataset = data_set.create_dataset(dataset_name = "Temp", dataset_type = "Temp", group_name = self.temp_group)
+ self.dataset = data_set.create_dataset(
+ dataset_name="Temp", dataset_type="Temp", group_name=self.temp_group)
self.this_trait = create_trait(dataset=self.dataset,
name=self.trait_id,
cellid=None)
self.trait_vals = Redis.get(self.trait_id).split()
- self.admin_status = check_owner_or_admin(dataset=self.dataset, trait_id=self.trait_id)
+ self.admin_status = check_owner_or_admin(
+ dataset=self.dataset, trait_id=self.trait_id)
- #ZS: Get verify/rna-seq link URLs
+ # ZS: Get verify/rna-seq link URLs
try:
blatsequence = self.this_trait.blatseq
if not blatsequence:
- #XZ, 06/03/2009: ProbeSet name is not unique among platforms. We should use ProbeSet Id instead.
+ # XZ, 06/03/2009: ProbeSet name is not unique among platforms. We should use ProbeSet Id instead.
query1 = """SELECT Probe.Sequence, Probe.Name
FROM Probe, ProbeSet, ProbeSetFreeze, ProbeSetXRef
WHERE ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND
@@ -91,10 +99,10 @@ class ShowTrait(object):
if int(seqt[1][-1]) % 2 == 1:
blatsequence += string.strip(seqt[0])
- #--------Hongqiang add this part in order to not only blat ProbeSet, but also blat Probe
+ # --------Hongqiang add this part in order to not only blat ProbeSet, but also blat Probe
blatsequence = '%3E' + self.this_trait.name + '%0A' + blatsequence + '%0A'
- #XZ, 06/03/2009: ProbeSet name is not unique among platforms. We should use ProbeSet Id instead.
+ # XZ, 06/03/2009: ProbeSet name is not unique among platforms. We should use ProbeSet Id instead.
query2 = """SELECT Probe.Sequence, Probe.Name
FROM Probe, ProbeSet, ProbeSetFreeze, ProbeSetXRef
WHERE ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND
@@ -105,24 +113,29 @@ class ShowTrait(object):
seqs = g.db.execute(query2).fetchall()
for seqt in seqs:
- if int(seqt[1][-1]) %2 == 1:
- blatsequence += '%3EProbe_' + seqt[1].strip() + '%0A' + seqt[0].strip() + '%0A'
+ if int(seqt[1][-1]) % 2 == 1:
+ blatsequence += '%3EProbe_' + \
+ seqt[1].strip() + '%0A' + seqt[0].strip() + '%0A'
if self.dataset.group.species == "rat":
- self.UCSC_BLAT_URL = webqtlConfig.UCSC_BLAT % ('rat', 'rn6', blatsequence)
+ self.UCSC_BLAT_URL = webqtlConfig.UCSC_BLAT % (
+ 'rat', 'rn6', blatsequence)
self.UTHSC_BLAT_URL = ""
elif self.dataset.group.species == "mouse":
- self.UCSC_BLAT_URL = webqtlConfig.UCSC_BLAT % ('mouse', 'mm10', blatsequence)
- self.UTHSC_BLAT_URL = webqtlConfig.UTHSC_BLAT % ('mouse', 'mm10', blatsequence)
+ self.UCSC_BLAT_URL = webqtlConfig.UCSC_BLAT % (
+ 'mouse', 'mm10', blatsequence)
+ self.UTHSC_BLAT_URL = webqtlConfig.UTHSC_BLAT % (
+ 'mouse', 'mm10', blatsequence)
elif self.dataset.group.species == "human":
- self.UCSC_BLAT_URL = webqtlConfig.UCSC_BLAT % ('human', 'hg38', blatsequence)
+ self.UCSC_BLAT_URL = webqtlConfig.UCSC_BLAT % (
+ 'human', 'hg38', blatsequence)
self.UTHSC_BLAT_URL = ""
else:
self.UCSC_BLAT_URL = ""
self.UTHSC_BLAT_URL = ""
except:
- self.UCSC_BLAT_URL = ""
- self.UTHSC_BLAT_URL = ""
+ self.UCSC_BLAT_URL = ""
+ self.UTHSC_BLAT_URL = ""
if self.dataset.type == "ProbeSet":
self.show_probes = "True"
@@ -136,7 +149,8 @@ class ShowTrait(object):
# Get nearest marker for composite mapping
if not self.temp_trait:
if check_if_attr_exists(self.this_trait, 'locus_chr') and self.dataset.type != "Geno" and self.dataset.type != "Publish":
- self.nearest_marker = get_nearest_marker(self.this_trait, self.dataset)
+ self.nearest_marker = get_nearest_marker(
+ self.this_trait, self.dataset)
else:
self.nearest_marker = ""
@@ -159,22 +173,25 @@ class ShowTrait(object):
categorical_var_list = []
if not self.temp_trait:
# ZS: Only using first samplelist, since I think mapping only uses those samples
- categorical_var_list = get_categorical_variables(self.this_trait, self.sample_groups[0])
+ categorical_var_list = get_categorical_variables(
+ self.this_trait, self.sample_groups[0])
# ZS: Get list of chromosomes to select for mapping
self.chr_list = [["All", -1]]
for i, this_chr in enumerate(self.dataset.species.chromosomes.chromosomes):
- self.chr_list.append([self.dataset.species.chromosomes.chromosomes[this_chr].name, i])
+ self.chr_list.append(
+ [self.dataset.species.chromosomes.chromosomes[this_chr].name, i])
self.genofiles = self.dataset.group.get_genofiles()
# ZS: No need to grab scales from .geno file unless it's using
# a mapping method that reads .geno files
- if "QTLReaper" or "R/qtl" in dataset.group.mapping_names:
+ if "QTLReaper" or "R/qtl" in dataset.group.mapping_names:
if self.genofiles:
self.scales_in_geno = get_genotype_scales(self.genofiles)
else:
- self.scales_in_geno = get_genotype_scales(self.dataset.group.name + ".geno")
+ self.scales_in_geno = get_genotype_scales(
+ self.dataset.group.name + ".geno")
else:
self.scales_in_geno = {}
@@ -211,7 +228,8 @@ class ShowTrait(object):
sample_column_width = max_samplename_width * 8
- self.stats_table_width, self.trait_table_width = get_table_widths(self.sample_groups, sample_column_width, self.has_num_cases)
+ self.stats_table_width, self.trait_table_width = get_table_widths(
+ self.sample_groups, sample_column_width, self.has_num_cases)
if self.num_values >= 5000:
self.maf = 0.01
@@ -242,9 +260,9 @@ class ShowTrait(object):
hddn['dataset'] = self.dataset.name
hddn['temp_trait'] = False
if self.temp_trait:
- hddn['temp_trait'] = True
- hddn['group'] = self.temp_group
- hddn['species'] = self.temp_species
+ hddn['temp_trait'] = True
+ hddn['group'] = self.temp_group
+ hddn['species'] = self.temp_species
hddn['use_outliers'] = False
hddn['method'] = "gemma"
hddn['selected_chr'] = -1
@@ -264,41 +282,46 @@ class ShowTrait(object):
hddn['export_data'] = ""
hddn['export_format'] = "excel"
if len(self.scales_in_geno) < 2:
- hddn['mapping_scale'] = self.scales_in_geno[list(self.scales_in_geno.keys())[0]][0][0]
+ hddn['mapping_scale'] = self.scales_in_geno[list(
+ self.scales_in_geno.keys())[0]][0][0]
# We'll need access to this_trait and hddn in the Jinja2
# Template, so we put it inside self
self.hddn = hddn
- js_data = dict(trait_id = self.trait_id,
- trait_symbol = trait_symbol,
- short_description = short_description,
- unit_type = trait_units,
- dataset_type = self.dataset.type,
- species = self.dataset.group.species,
- scales_in_geno = self.scales_in_geno,
- data_scale = self.dataset.data_scale,
- sample_group_types = self.sample_group_types,
- sample_lists = sample_lists,
- se_exists = self.sample_groups[0].se_exists,
- has_num_cases = self.has_num_cases,
- attributes = self.sample_groups[0].attributes,
- categorical_attr_exists = self.categorical_attr_exists,
- categorical_vars = ",".join(categorical_var_list),
- num_values = self.num_values,
- qnorm_values = self.qnorm_vals,
- zscore_values = self.z_scores,
- sample_column_width = sample_column_width,
- temp_uuid = self.temp_uuid)
+ js_data = dict(trait_id=self.trait_id,
+ trait_symbol=trait_symbol,
+ short_description=short_description,
+ unit_type=trait_units,
+ dataset_type=self.dataset.type,
+ species=self.dataset.group.species,
+ scales_in_geno=self.scales_in_geno,
+ data_scale=self.dataset.data_scale,
+ sample_group_types=self.sample_group_types,
+ sample_lists=sample_lists,
+ se_exists=self.sample_groups[0].se_exists,
+ has_num_cases=self.has_num_cases,
+ attributes=self.sample_groups[0].attributes,
+ categorical_attr_exists=self.categorical_attr_exists,
+ categorical_vars=",".join(categorical_var_list),
+ num_values=self.num_values,
+ qnorm_values=self.qnorm_vals,
+ zscore_values=self.z_scores,
+ sample_column_width=sample_column_width,
+ temp_uuid=self.temp_uuid)
self.js_data = js_data
def get_external_links(self):
# ZS: There's some weirdness here because some fields don't
# exist while others are empty strings
- self.pubmed_link = webqtlConfig.PUBMEDLINK_URL % self.this_trait.pubmed_id if check_if_attr_exists(self.this_trait, 'pubmed_id') else None
- self.ncbi_gene_link = webqtlConfig.NCBI_LOCUSID % self.this_trait.geneid if check_if_attr_exists(self.this_trait, 'geneid') else None
- self.omim_link = webqtlConfig.OMIM_ID % self.this_trait.omim if check_if_attr_exists(self.this_trait, 'omim') else None
- self.homologene_link = webqtlConfig.HOMOLOGENE_ID % self.this_trait.homologeneid if check_if_attr_exists(self.this_trait, 'homologeneid') else None
+ self.pubmed_link = webqtlConfig.PUBMEDLINK_URL % self.this_trait.pubmed_id if check_if_attr_exists(
+ self.this_trait, 'pubmed_id') else None
+ self.ncbi_gene_link = webqtlConfig.NCBI_LOCUSID % self.this_trait.geneid if check_if_attr_exists(
+ self.this_trait, 'geneid') else None
+ self.omim_link = webqtlConfig.OMIM_ID % self.this_trait.omim if check_if_attr_exists(
+ self.this_trait, 'omim') else None
+ self.homologene_link = webqtlConfig.HOMOLOGENE_ID % self.this_trait.homologeneid if check_if_attr_exists(
+ self.this_trait, 'homologeneid') else None
self.genbank_link = None
if check_if_attr_exists(self.this_trait, 'genbankid'):
@@ -322,11 +345,14 @@ class ShowTrait(object):
self.protein_atlas_link = webqtlConfig.PROTEIN_ATLAS_URL % self.this_trait.symbol
if self.dataset.group.species == "mouse" or self.dataset.group.species == "human":
- self.rgd_link = webqtlConfig.RGD_URL % (self.this_trait.symbol, self.dataset.group.species.capitalize())
+ self.rgd_link = webqtlConfig.RGD_URL % (
+ self.this_trait.symbol, self.dataset.group.species.capitalize())
if self.dataset.group.species == "mouse":
- self.genemania_link = webqtlConfig.GENEMANIA_URL % ("mus-musculus", self.this_trait.symbol)
+ self.genemania_link = webqtlConfig.GENEMANIA_URL % (
+ "mus-musculus", self.this_trait.symbol)
else:
- self.genemania_link = webqtlConfig.GENEMANIA_URL % ("homo-sapiens", self.this_trait.symbol)
+ self.genemania_link = webqtlConfig.GENEMANIA_URL % (
+ "homo-sapiens", self.this_trait.symbol)
if self.dataset.group.species == "mouse":
self.aba_link = webqtlConfig.ABA_URL % self.this_trait.symbol
@@ -344,12 +370,16 @@ class ShowTrait(object):
if chr and transcript_start and transcript_end and self.this_trait.refseq_transcriptid:
transcript_start = int(transcript_start*1000000)
transcript_end = int(transcript_end*1000000)
- self.ucsc_blat_link = webqtlConfig.UCSC_REFSEQ % ('mm10', self.this_trait.refseq_transcriptid, chr, transcript_start, transcript_end)
+ self.ucsc_blat_link = webqtlConfig.UCSC_REFSEQ % (
+ 'mm10', self.this_trait.refseq_transcriptid, chr, transcript_start, transcript_end)
if self.dataset.group.species == "rat":
- self.rgd_link = webqtlConfig.RGD_URL % (self.this_trait.symbol, self.dataset.group.species.capitalize())
- self.phenogen_link = webqtlConfig.PHENOGEN_URL % (self.this_trait.symbol)
- self.genemania_link = webqtlConfig.GENEMANIA_URL % ("rattus-norvegicus", self.this_trait.symbol)
+ self.rgd_link = webqtlConfig.RGD_URL % (
+ self.this_trait.symbol, self.dataset.group.species.capitalize())
+ self.phenogen_link = webqtlConfig.PHENOGEN_URL % (
+ self.this_trait.symbol)
+ self.genemania_link = webqtlConfig.GENEMANIA_URL % (
+ "rattus-norvegicus", self.this_trait.symbol)
query = """SELECT kgID, chromosome, txStart, txEnd
FROM GeneList_rn33
@@ -362,12 +392,15 @@ class ShowTrait(object):
kgId = chr = transcript_start = transcript_end = None
if chr and transcript_start and transcript_end and kgId:
- transcript_start = int(transcript_start*1000000) # Convert to bases from megabases
+ # Convert to bases from megabases
+ transcript_start = int(transcript_start*1000000)
transcript_end = int(transcript_end*1000000)
- self.ucsc_blat_link = webqtlConfig.UCSC_REFSEQ % ('rn6', kgId, chr, transcript_start, transcript_end)
+ self.ucsc_blat_link = webqtlConfig.UCSC_REFSEQ % (
+ 'rn6', kgId, chr, transcript_start, transcript_end)
if self.this_trait.geneid and (self.dataset.group.species == "mouse" or self.dataset.group.species == "rat" or self.dataset.group.species == "human"):
- self.biogps_link = webqtlConfig.BIOGPS_URL % (self.dataset.group.species, self.this_trait.geneid)
+ self.biogps_link = webqtlConfig.BIOGPS_URL % (
+ self.dataset.group.species, self.this_trait.geneid)
self.gemma_link = webqtlConfig.GEMMA_URL % self.this_trait.geneid
if self.dataset.group.species == "human":
@@ -388,40 +421,43 @@ class ShowTrait(object):
if self.temp_trait == True:
dataset_menu = data_set.datasets(this_group)
else:
- dataset_menu = data_set.datasets(this_group, self.dataset.group)
+ dataset_menu = data_set.datasets(
+ this_group, self.dataset.group)
dataset_menu_selected = None
if len(dataset_menu):
if self.dataset:
dataset_menu_selected = self.dataset.name
- return_results_menu = (100, 200, 500, 1000, 2000, 5000, 10000, 15000, 20000)
+ return_results_menu = (100, 200, 500, 1000,
+ 2000, 5000, 10000, 15000, 20000)
return_results_menu_selected = 500
- self.corr_tools = dict(dataset_menu = dataset_menu,
- dataset_menu_selected = dataset_menu_selected,
- return_results_menu = return_results_menu,
- return_results_menu_selected = return_results_menu_selected,)
+ self.corr_tools = dict(dataset_menu=dataset_menu,
+ dataset_menu_selected=dataset_menu_selected,
+ return_results_menu=return_results_menu,
+ return_results_menu_selected=return_results_menu_selected,)
def make_sample_lists(self):
all_samples_ordered = self.dataset.group.all_samples_ordered()
-
+
parent_f1_samples = []
if self.dataset.group.parlist and self.dataset.group.f1list:
parent_f1_samples = self.dataset.group.parlist + self.dataset.group.f1list
primary_sample_names = list(all_samples_ordered)
-
if not self.temp_trait:
other_sample_names = []
for sample in list(self.this_trait.data.keys()):
if (self.this_trait.data[sample].name2 != self.this_trait.data[sample].name):
if ((self.this_trait.data[sample].name2 in primary_sample_names) and
- (self.this_trait.data[sample].name not in primary_sample_names)):
- primary_sample_names.append(self.this_trait.data[sample].name)
- primary_sample_names.remove(self.this_trait.data[sample].name2)
+ (self.this_trait.data[sample].name not in primary_sample_names)):
+ primary_sample_names.append(
+ self.this_trait.data[sample].name)
+ primary_sample_names.remove(
+ self.this_trait.data[sample].name2)
all_samples_set = set(all_samples_ordered)
if sample not in all_samples_set:
@@ -440,34 +476,34 @@ class ShowTrait(object):
else:
primary_header = "Samples"
- primary_samples = SampleList(dataset = self.dataset,
- sample_names=primary_sample_names,
- this_trait=self.this_trait,
- sample_group_type='primary',
- header=primary_header)
+ primary_samples = SampleList(dataset=self.dataset,
+ sample_names=primary_sample_names,
+ this_trait=self.this_trait,
+ sample_group_type='primary',
+ header=primary_header)
# if other_sample_names and self.dataset.group.species !=
# "human" and self.dataset.group.name != "CFW":
if len(other_sample_names) > 0:
- other_sample_names.sort() #Sort other samples
+ other_sample_names.sort() # Sort other samples
if parent_f1_samples:
other_sample_names = parent_f1_samples + other_sample_names
other_samples = SampleList(dataset=self.dataset,
- sample_names=other_sample_names,
- this_trait=self.this_trait,
- sample_group_type='other',
- header="Other")
+ sample_names=other_sample_names,
+ this_trait=self.this_trait,
+ sample_group_type='other',
+ header="Other")
self.sample_groups = (primary_samples, other_samples)
else:
self.sample_groups = (primary_samples,)
else:
- primary_samples = SampleList(dataset = self.dataset,
- sample_names=primary_sample_names,
- this_trait=self.trait_vals,
- sample_group_type='primary',
- header="%s Only" % (self.dataset.group.name))
+ primary_samples = SampleList(dataset=self.dataset,
+ sample_names=primary_sample_names,
+ this_trait=self.trait_vals,
+ sample_group_type='primary',
+ header="%s Only" % (self.dataset.group.name))
self.sample_groups = (primary_samples,)
self.primary_sample_names = primary_sample_names
@@ -622,8 +658,10 @@ def get_ncbi_summary(this_trait):
# ZS: Need to switch this try/except to something that checks
# the output later
try:
- response = requests.get("http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=gene&id=%s&retmode=json" % this_trait.geneid)
- summary = json.loads(response.content)['result'][this_trait.geneid]['summary']
+ response = requests.get(
+ "http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=gene&id=%s&retmode=json" % this_trait.geneid)
+ summary = json.loads(response.content)[
+ 'result'][this_trait.geneid]['summary']
return summary
except:
return None
@@ -639,13 +677,15 @@ def get_categorical_variables(this_trait, sample_list):
attribute_vals = []
for sample_name in list(this_trait.data.keys()):
if sample_list.attributes[attribute].name in this_trait.data[sample_name].extra_attributes:
- attribute_vals.append(this_trait.data[sample_name].extra_attributes[sample_list.attributes[attribute].name])
+ attribute_vals.append(
+ this_trait.data[sample_name].extra_attributes[sample_list.attributes[attribute].name])
else:
attribute_vals.append("N/A")
num_distinct = len(set(attribute_vals))
if num_distinct < 10:
- categorical_var_list.append(sample_list.attributes[attribute].name)
+ categorical_var_list.append(
+ sample_list.attributes[attribute].name)
return categorical_var_list
@@ -655,7 +695,8 @@ def get_genotype_scales(genofiles):
if isinstance(genofiles, list):
for the_file in genofiles:
file_location = the_file['location']
- geno_scales[file_location] = get_scales_from_genofile(file_location)
+ geno_scales[file_location] = get_scales_from_genofile(
+ file_location)
else:
geno_scales[genofiles] = get_scales_from_genofile(genofiles)