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-rw-r--r--gn2/wqflask/api/__init__.py0
-rw-r--r--gn2/wqflask/api/correlation.py244
-rw-r--r--gn2/wqflask/api/gen_menu.py217
-rw-r--r--gn2/wqflask/api/jobs.py54
-rw-r--r--gn2/wqflask/api/mapping.py186
-rw-r--r--gn2/wqflask/api/markdown.py186
-rw-r--r--gn2/wqflask/api/router.py1037
7 files changed, 1924 insertions, 0 deletions
diff --git a/gn2/wqflask/api/__init__.py b/gn2/wqflask/api/__init__.py
new file mode 100644
index 00000000..e69de29b
--- /dev/null
+++ b/gn2/wqflask/api/__init__.py
diff --git a/gn2/wqflask/api/correlation.py b/gn2/wqflask/api/correlation.py
new file mode 100644
index 00000000..090d13ac
--- /dev/null
+++ b/gn2/wqflask/api/correlation.py
@@ -0,0 +1,244 @@
+import collections
+import scipy
+import numpy
+
+from gn2.base import data_set
+from gn2.base.trait import create_trait, retrieve_sample_data
+from gn2.utility import corr_result_helpers
+from gn2.utility.tools import get_setting
+from gn2.wqflask.correlation import correlation_functions
+from gn2.wqflask.database import database_connection
+
+def do_correlation(start_vars):
+ if 'db' not in start_vars:
+ raise ValueError("'db' not found!")
+ if 'target_db' not in start_vars:
+ raise ValueError("'target_db' not found!")
+ if 'trait_id' not in start_vars:
+ raise ValueError("'trait_id' not found!")
+
+ this_dataset = data_set.create_dataset(dataset_name=start_vars['db'])
+ target_dataset = data_set.create_dataset(
+ dataset_name=start_vars['target_db'])
+ this_trait = create_trait(dataset=this_dataset,
+ name=start_vars['trait_id'])
+ this_trait = retrieve_sample_data(this_trait, this_dataset)
+
+ corr_params = init_corr_params(start_vars)
+
+ corr_results = calculate_results(
+ this_trait, this_dataset, target_dataset, corr_params)
+
+ final_results = []
+ for _trait_counter, trait in enumerate(list(corr_results.keys())[:corr_params['return_count']]):
+ if corr_params['type'] == "tissue":
+ [sample_r, num_overlap, sample_p, symbol] = corr_results[trait]
+ result_dict = {
+ "trait": trait,
+ "sample_r": sample_r,
+ "#_strains": num_overlap,
+ "p_value": sample_p,
+ "symbol": symbol
+ }
+ elif corr_params['type'] == "literature" or corr_params['type'] == "lit":
+ [gene_id, sample_r] = corr_results[trait]
+ result_dict = {
+ "trait": trait,
+ "sample_r": sample_r,
+ "gene_id": gene_id
+ }
+ else:
+ [sample_r, sample_p, num_overlap] = corr_results[trait]
+ result_dict = {
+ "trait": trait,
+ "sample_r": sample_r,
+ "#_strains": num_overlap,
+ "p_value": sample_p
+ }
+ final_results.append(result_dict)
+ return final_results
+
+
+def calculate_results(this_trait, this_dataset, target_dataset, corr_params):
+ corr_results = {}
+
+ target_dataset.get_trait_data()
+
+ if corr_params['type'] == "tissue":
+ trait_symbol_dict = this_dataset.retrieve_genes("Symbol")
+ corr_results = do_tissue_correlation_for_all_traits(
+ this_trait, trait_symbol_dict, corr_params)
+ sorted_results = collections.OrderedDict(sorted(list(corr_results.items()),
+ key=lambda t: -abs(t[1][1])))
+ # ZS: Just so a user can use either "lit" or "literature"
+ elif corr_params['type'] == "literature" or corr_params['type'] == "lit":
+ trait_geneid_dict = this_dataset.retrieve_genes("GeneId")
+ corr_results = do_literature_correlation_for_all_traits(
+ this_trait, this_dataset, trait_geneid_dict, corr_params)
+ sorted_results = collections.OrderedDict(sorted(list(corr_results.items()),
+ key=lambda t: -abs(t[1][1])))
+ else:
+ for target_trait, target_vals in list(target_dataset.trait_data.items()):
+ result = get_sample_r_and_p_values(
+ this_trait, this_dataset, target_vals, target_dataset, corr_params['type'])
+ if result is not None:
+ corr_results[target_trait] = result
+
+ sorted_results = collections.OrderedDict(
+ sorted(list(corr_results.items()), key=lambda t: -abs(t[1][0])))
+
+ return sorted_results
+
+
+def do_tissue_correlation_for_all_traits(this_trait, trait_symbol_dict, corr_params, tissue_dataset_id=1):
+ # Gets tissue expression values for the primary trait
+ primary_trait_tissue_vals_dict = correlation_functions.get_trait_symbol_and_tissue_values(
+ symbol_list=[this_trait.symbol])
+
+ if this_trait.symbol.lower() in primary_trait_tissue_vals_dict:
+ primary_trait_tissue_values = primary_trait_tissue_vals_dict[this_trait.symbol.lower(
+ )]
+
+ corr_result_tissue_vals_dict = correlation_functions.get_trait_symbol_and_tissue_values(
+ symbol_list=list(trait_symbol_dict.values()))
+
+ tissue_corr_data = {}
+ for trait, symbol in list(trait_symbol_dict.items()):
+ if symbol and symbol.lower() in corr_result_tissue_vals_dict:
+ this_trait_tissue_values = corr_result_tissue_vals_dict[symbol.lower(
+ )]
+
+ result = correlation_functions.cal_zero_order_corr_for_tiss(primary_trait_tissue_values,
+ this_trait_tissue_values,
+ corr_params['method'])
+
+ tissue_corr_data[trait] = [
+ result[0], result[1], result[2], symbol]
+
+ return tissue_corr_data
+
+
+def do_literature_correlation_for_all_traits(this_trait, target_dataset, trait_geneid_dict, corr_params):
+ input_trait_mouse_gene_id = convert_to_mouse_gene_id(
+ target_dataset.group.species.lower(), this_trait.geneid)
+
+ lit_corr_data = {}
+ for trait, gene_id in list(trait_geneid_dict.items()):
+ mouse_gene_id = convert_to_mouse_gene_id(
+ target_dataset.group.species.lower(), gene_id)
+
+ if mouse_gene_id and str(mouse_gene_id).find(";") == -1:
+ result = ""
+ with database_connection(get_setting("SQL_URI")) as conn:
+ with conn.cursor() as cursor:
+ cursor.execute(
+ ("SELECT value FROM LCorrRamin3 "
+ "WHERE GeneId1=%s AND GeneId2=%s"),
+ (mouse_gene_id,
+ input_trait_mouse_gene_id))
+ result = cursor.fetchone()
+ if not result:
+ cursor.execute(
+ ("SELECT value FROM LCorrRamin3 "
+ "WHERE GeneId2=%s AND GeneId1=%s"),
+ (mouse_gene_id,
+ input_trait_mouse_gene_id))
+ result = cursor.fetchone()
+ if result:
+ lit_corr = result[0]
+ lit_corr_data[trait] = [gene_id, lit_corr]
+ else:
+ lit_corr_data[trait] = [gene_id, 0]
+ else:
+ lit_corr_data[trait] = [gene_id, 0]
+
+ return lit_corr_data
+
+
+def get_sample_r_and_p_values(this_trait, this_dataset, target_vals, target_dataset, type):
+ """
+ Calculates the sample r (or rho) and p-value
+
+ Given a primary trait and a target trait's sample values,
+ calculates either the pearson r or spearman rho and the p-value
+ using the corresponding scipy functions.
+ """
+
+ this_trait_vals = []
+ shared_target_vals = []
+ for i, sample in enumerate(target_dataset.group.samplelist):
+ if sample in this_trait.data:
+ this_sample_value = this_trait.data[sample].value
+ target_sample_value = target_vals[i]
+ this_trait_vals.append(this_sample_value)
+ shared_target_vals.append(target_sample_value)
+
+ this_trait_vals, shared_target_vals, num_overlap = corr_result_helpers.normalize_values(
+ this_trait_vals, shared_target_vals)
+
+ if type == 'pearson':
+ sample_r, sample_p = scipy.stats.pearsonr(
+ this_trait_vals, shared_target_vals)
+ else:
+ sample_r, sample_p = scipy.stats.spearmanr(
+ this_trait_vals, shared_target_vals)
+
+ if num_overlap > 5:
+ if numpy.isnan(sample_r):
+ return None
+ else:
+ return [sample_r, sample_p, num_overlap]
+
+
+def convert_to_mouse_gene_id(species=None, gene_id=None):
+ """If the species is rat or human, translate the gene_id to the mouse geneid
+
+ If there is no input gene_id or there's no corresponding mouse gene_id, return None
+
+ """
+ if not gene_id:
+ return None
+
+ mouse_gene_id = None
+ with database_connection(get_setting("SQL_URI")) as conn:
+ with conn.cursor() as cursor:
+ if species == 'mouse':
+ mouse_gene_id = gene_id
+ elif species == 'rat':
+ cursor.execute(
+ ("SELECT mouse FROM GeneIDXRef "
+ "WHERE rat=%s"), gene_id)
+ result = cursor.fetchone()
+ if result:
+ mouse_gene_id = result[0]
+ elif species == 'human':
+ cursor.execute(
+ "SELECT mouse FROM GeneIDXRef "
+ "WHERE human=%s", gene_id)
+ result = cursor.fetchone()
+ if result:
+ mouse_gene_id = result[0]
+ return mouse_gene_id
+
+
+def init_corr_params(start_vars):
+ method = "pearson"
+ if 'method' in start_vars:
+ method = start_vars['method']
+
+ type = "sample"
+ if 'type' in start_vars:
+ type = start_vars['type']
+
+ return_count = 500
+ if 'return_count' in start_vars:
+ assert(start_vars['return_count'].isdigit())
+ return_count = int(start_vars['return_count'])
+
+ corr_params = {
+ 'method': method,
+ 'type': type,
+ 'return_count': return_count
+ }
+
+ return corr_params
diff --git a/gn2/wqflask/api/gen_menu.py b/gn2/wqflask/api/gen_menu.py
new file mode 100644
index 00000000..45d5739e
--- /dev/null
+++ b/gn2/wqflask/api/gen_menu.py
@@ -0,0 +1,217 @@
+from gn3.db.species import get_all_species
+
+def gen_dropdown_json(conn):
+ """Generates and outputs (as json file) the data for the main dropdown menus on
+ the home page
+ """
+ species = get_all_species(conn)
+ groups = get_groups(species, conn)
+ types = get_types(groups, conn)
+ datasets = get_datasets(types, conn)
+ return dict(species=species,
+ groups=groups,
+ types=types,
+ datasets=datasets)
+
+
+def get_groups(species, conn):
+ """Build groups list"""
+ groups = {}
+ with conn.cursor() as cursor:
+ for species_name, _species_full_name in species:
+ groups[species_name] = []
+ query = ("SELECT InbredSet.Name, InbredSet.FullName, "
+ "IFNULL(InbredSet.Family, 'None') "
+ "FROM InbredSet, Species WHERE Species.Name = '{}' "
+ "AND InbredSet.SpeciesId = Species.Id GROUP by "
+ "InbredSet.Name ORDER BY IFNULL(InbredSet.FamilyOrder, "
+ "InbredSet.FullName) ASC, IFNULL(InbredSet.Family, "
+ "InbredSet.FullName) ASC, InbredSet.FullName ASC, "
+ "InbredSet.MenuOrderId ASC").format(species_name)
+ cursor.execute(query)
+ results = cursor.fetchall()
+ for result in results:
+ family_name = "Family:" + str(result[2])
+ groups[species_name].append(
+ [str(result[0]), str(result[1]), family_name])
+ return groups
+
+
+def get_types(groups, conn):
+ """Build types list"""
+ types = {}
+
+ for species, group_dict in list(groups.items()):
+ types[species] = {}
+ for group_name, _group_full_name, _family_name in group_dict:
+ if phenotypes_exist(group_name, conn):
+ types[species][group_name] = [
+ ("Phenotypes", "Traits and Cofactors", "Phenotypes")]
+ if genotypes_exist(group_name, conn):
+ if group_name in types[species]:
+ types[species][group_name] += [
+ ("Genotypes", "DNA Markers and SNPs", "Genotypes")]
+ else:
+ types[species][group_name] = [
+ ("Genotypes", "DNA Markers and SNPs", "Genotypes")]
+ if group_name in types[species]:
+ types_list = build_types(species, group_name, conn)
+ if len(types_list) > 0:
+ types[species][group_name] += types_list
+ else:
+ types_list = build_types(species, group_name, conn)
+ if len(types_list) > 0:
+ types[species][group_name] = types_list
+ else:
+ types[species].pop(group_name, None)
+ groups[species] = list(
+ group for group in groups[species]
+ if group[0] != group_name)
+ return types
+
+
+def phenotypes_exist(group_name, conn):
+ results = []
+ with conn.cursor() as cursor:
+ cursor.execute(
+ ("SELECT Name FROM PublishFreeze "
+ "WHERE PublishFreeze.Name = "
+ "'{}'").format(group_name + "Publish"))
+ results = cursor.fetchone()
+ return bool(results)
+
+
+def genotypes_exist(group_name, conn):
+ with conn.cursor() as cursor:
+ cursor.execute(
+ ("SELECT Name FROM GenoFreeze " +
+ "WHERE GenoFreeze.Name = '{}'").format(
+ group_name + "Geno"))
+ results = cursor.fetchone()
+ return bool(results)
+
+
+def build_types(species, group, conn):
+ """Fetches tissues
+
+ Gets the tissues with data for this species/group
+ (all types except phenotype/genotype are tissues)
+
+ """
+
+ query = ("SELECT DISTINCT Tissue.Name "
+ "FROM ProbeFreeze, ProbeSetFreeze, InbredSet, "
+ "Tissue, Species WHERE Species.Name = '{0}' "
+ "AND Species.Id = InbredSet.SpeciesId AND "
+ "InbredSet.Name = '{1}' AND ProbeFreeze.TissueId = "
+ "Tissue.Id AND ProbeFreeze.InbredSetId = InbredSet.Id "
+ "AND ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id "
+ "ORDER BY Tissue.Name").format(species, group)
+
+ results = []
+ with conn.cursor() as cursor:
+ cursor.execute(query)
+ for result in cursor.fetchall():
+ if bool(result):
+ these_datasets = build_datasets(species,
+ group, result[0], conn)
+ if len(these_datasets) > 0:
+ results.append([str(result[0]), str(result[0]),
+ "Molecular Traits"])
+ return results
+
+
+def get_datasets(types, conn):
+ """Build datasets list"""
+ datasets = {}
+ for species, group_dict in list(types.items()):
+ datasets[species] = {}
+ for group, type_list in list(group_dict.items()):
+ datasets[species][group] = {}
+ for type_name in type_list:
+ these_datasets = build_datasets(species, group,
+ type_name[0], conn)
+ if bool(these_datasets):
+ datasets[species][group][type_name[0]] = these_datasets
+
+ return datasets
+
+
+def build_datasets(species, group, type_name, conn):
+ """Gets dataset names from database"""
+ dataset_text = dataset_value = None
+ datasets = []
+ with conn.cursor() as cursor:
+ if type_name == "Phenotypes":
+ cursor.execute(
+ ("SELECT InfoFiles.GN_AccesionId, PublishFreeze.Name, "
+ "PublishFreeze.FullName FROM InfoFiles, PublishFreeze, "
+ "InbredSet WHERE InbredSet.Name = '{}' AND "
+ "PublishFreeze.InbredSetId = InbredSet.Id AND "
+ "InfoFiles.InfoPageName = PublishFreeze.Name "
+ "ORDER BY PublishFreeze.CreateTime ASC").format(group))
+ results = cursor.fetchall()
+ if bool(results):
+ for result in results:
+ dataset_id = str(result[0])
+ dataset_value = str(result[1])
+ dataset_text = str(result[2])
+ if group == 'MDP':
+ dataset_text = "Mouse Phenome Database"
+
+ datasets.append([dataset_id, dataset_value, dataset_text])
+ else:
+ cursor.execute(
+ ("SELECT PublishFreeze.Name, PublishFreeze.FullName "
+ "FROM PublishFreeze, InbredSet "
+ "WHERE InbredSet.Name = '{}' AND "
+ "PublishFreeze.InbredSetId = InbredSet.Id "
+ "ORDER BY PublishFreeze.CreateTime ASC")
+ .format(group))
+ result = cursor.fetchone()
+ dataset_id = "None"
+ dataset_value = str(result[0])
+ dataset_text = str(result[1])
+ datasets.append([dataset_id, dataset_value, dataset_text])
+
+ elif type_name == "Genotypes":
+ cursor.execute(
+ ("SELECT InfoFiles.GN_AccesionId "
+ "FROM InfoFiles, GenoFreeze, InbredSet "
+ "WHERE InbredSet.Name = '{}' AND "
+ "GenoFreeze.InbredSetId = InbredSet.Id AND "
+ "InfoFiles.InfoPageName = GenoFreeze.ShortName "
+ "ORDER BY GenoFreeze.CreateTime "
+ "DESC").format(group))
+ results = cursor.fetchone()
+ dataset_id = "None"
+ if bool(results):
+ dataset_id = str(results[0])
+
+ dataset_value = "%sGeno" % group
+ dataset_text = "%s Genotypes" % group
+ datasets.append([dataset_id, dataset_value, dataset_text])
+
+ else: # for mRNA expression/ProbeSet
+ cursor.execute(
+ ("SELECT ProbeSetFreeze.Id, ProbeSetFreeze.Name, "
+ "ProbeSetFreeze.FullName FROM ProbeSetFreeze, "
+ "ProbeFreeze, InbredSet, Tissue, Species WHERE "
+ "Species.Name = '{0}' AND Species.Id = "
+ "InbredSet.SpeciesId AND InbredSet.Name = '{1}' "
+ "AND ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id "
+ "AND Tissue.Name = '{2}' AND ProbeFreeze.TissueId = "
+ "Tissue.Id AND ProbeFreeze.InbredSetId = InbredSet.Id "
+ "AND ProbeSetFreeze.public > 0 "
+ "ORDER BY -ProbeSetFreeze.OrderList DESC, "
+ "ProbeSetFreeze.CreateTime "
+ "DESC").format(species, group, type_name))
+ results = cursor.fetchall()
+ datasets = []
+ for dataset_info in results:
+ this_dataset_info = []
+ for info in dataset_info:
+ this_dataset_info.append(str(info))
+ datasets.append(this_dataset_info)
+
+ return datasets
diff --git a/gn2/wqflask/api/jobs.py b/gn2/wqflask/api/jobs.py
new file mode 100644
index 00000000..7a948e1a
--- /dev/null
+++ b/gn2/wqflask/api/jobs.py
@@ -0,0 +1,54 @@
+import uuid
+from datetime import datetime
+
+from redis import Redis
+from pymonad.io import IO
+from flask import Blueprint, render_template
+
+from gn2.jobs.jobs import job
+
+jobs = Blueprint("jobs", __name__)
+
+@jobs.route("/debug/<uuid:job_id>")
+def debug_job(job_id: uuid.UUID):
+ """Display job data to assist in debugging."""
+ from gn2.utility.tools import REDIS_URL # Avoids circular import error
+
+ def __stream_to_lines__(stream):
+ removables = (
+ "Set global log level to", "runserver.py: ******",
+ "APPLICATION_ROOT:", "DB_", "DEBUG:", "ELASTICSEARCH_", "ENV:",
+ "EXPLAIN_TEMPLATE_LOADING:", "GEMMA_", "GENENETWORK_FILES",
+ "GITHUB_", "GN2_", "GN3_", "GN_", "HOME:", "JSONIFY_", "JS_",
+ "JSON_", "LOG_", "MAX_", "ORCID_", "PERMANENT_", "PLINK_",
+ "PREFERRED_URL_SCHEME", "PRESERVE_CONTEXT_ON_EXCEPTION",
+ "PROPAGATE_EXCEPTIONS", "REAPER_COMMAND", "REDIS_URL", "SECRET_",
+ "SECURITY_", "SEND_FILE_MAX_AGE_DEFAULT", "SERVER_", "SESSION_",
+ "SMTP_", "SQL_", "TEMPLATES_", "TESTING:", "TMPDIR", "TRAP_",
+ "USE_", "WEBSERVER_")
+ return tuple(filter(
+ lambda line: not any(line.startswith(item) for item in removables),
+ stream.split("\n")))
+
+ def __fmt_datetime(val):
+ return datetime.strptime(val, "%Y-%m-%dT%H:%M:%S.%f").strftime(
+ "%A, %d %B %Y at %H:%M:%S.%f")
+
+ def __render_debug_page__(job):
+ job_details = {key.replace("-", "_"): val for key,val in job.items()}
+ return render_template(
+ "jobs/debug.html",
+ **{
+ **job_details,
+ "request_received_time": __fmt_datetime(
+ job_details["request_received_time"]),
+ "stderr": __stream_to_lines__(job_details["stderr"]),
+ "stdout": __stream_to_lines__(job_details["stdout"])
+ })
+
+ with Redis.from_url(REDIS_URL, decode_responses=True) as rconn:
+ the_job = job(rconn, job_id)
+
+ return the_job.maybe(
+ render_template("jobs/no-such-job.html", job_id=job_id),
+ lambda job: __render_debug_page__(job))
diff --git a/gn2/wqflask/api/mapping.py b/gn2/wqflask/api/mapping.py
new file mode 100644
index 00000000..1e330963
--- /dev/null
+++ b/gn2/wqflask/api/mapping.py
@@ -0,0 +1,186 @@
+from gn2.base import data_set
+from gn2.base.trait import create_trait, retrieve_sample_data
+
+from gn2.wqflask.marker_regression import gemma_mapping, rqtl_mapping
+from gn2.wqflask.show_trait.show_trait import normf
+
+def do_mapping_for_api(start_vars):
+ if ('db' not in start_vars) or ("trait_id" not in start_vars):
+ raise ValueError("Mapping: db and trait_id are not in start_vars")
+
+ dataset = data_set.create_dataset(dataset_name=start_vars['db'])
+ dataset.group.get_markers()
+ this_trait = create_trait(dataset=dataset, name=start_vars['trait_id'])
+ this_trait = retrieve_sample_data(this_trait, dataset)
+
+ samples = []
+ vals = []
+
+ mapping_params = initialize_parameters(start_vars, dataset, this_trait)
+
+ genofile_samplelist = []
+ if mapping_params.get('genofile'):
+ dataset.group.genofile = mapping_params['genofile']
+ genofile_samplelist = get_genofile_samplelist(dataset)
+
+ if (len(genofile_samplelist) > 0):
+ samplelist = genofile_samplelist
+ for sample in samplelist:
+ in_trait_data = False
+ for item in this_trait.data:
+ if this_trait.data[item].name == sample:
+ value = str(this_trait.data[item].value)
+ samples.append(item)
+ vals.append(value)
+ in_trait_data = True
+ break
+ if not in_trait_data:
+ vals.append("x")
+ else:
+ samplelist = dataset.group.samplelist
+ for sample in samplelist:
+ in_trait_data = False
+ for item in this_trait.data:
+ if this_trait.data[item].name == sample:
+ value = str(this_trait.data[item].value)
+ samples.append(item)
+ vals.append(value)
+ in_trait_data = True
+ break
+ if not in_trait_data:
+ vals.append("x")
+
+ if mapping_params.get('transform') == "qnorm":
+ vals_minus_x = [float(val) for val in vals if val != "x"]
+ qnorm_vals = normf(vals_minus_x)
+ qnorm_vals_with_x = []
+ counter = 0
+ for val in vals:
+ if val == "x":
+ qnorm_vals_with_x.append("x")
+ else:
+ qnorm_vals_with_x.append(qnorm_vals[counter])
+ counter += 1
+
+ vals = qnorm_vals_with_x
+
+ # It seems to take an empty string as default. This should probably be changed.
+ covariates = ""
+
+ if mapping_params.get('mapping_method') == "gemma":
+ header_row = ["name", "chr", "Mb", "lod_score", "p_value"]
+ # gemma_mapping returns both results and the filename for LOCO, so need to only grab the former for api
+ if mapping_params.get('use_loco') == "True":
+ result_markers = gemma_mapping.run_gemma(
+ this_trait, dataset, samples, vals, covariates, mapping_params['use_loco'], mapping_params['maf'])[0]
+ else:
+ result_markers = gemma_mapping.run_gemma(
+ this_trait, dataset, samples, vals, covariates, mapping_params['use_loco'], mapping_params['maf'])
+ elif mapping_params.get('mapping_method') == "rqtl":
+ header_row = ["name", "chr", "cM", "lod_score"]
+ if mapping_params['num_perm'] > 0:
+ _sperm_output, _suggestive, _significant, result_markers = rqtl_mapping.run_rqtl(this_trait.name, vals, samples, dataset, None, "Mb", mapping_params['rqtl_model'],
+ mapping_params['rqtl_method'], mapping_params['num_perm'], None,
+ mapping_params['do_control'], mapping_params['control_marker'],
+ mapping_params['manhattan_plot'], None)
+ else:
+ result_markers = rqtl_mapping.run_rqtl(this_trait.name, vals, samples, dataset, None, "Mb", mapping_params['rqtl_model'],
+ mapping_params['rqtl_method'], mapping_params['num_perm'], None,
+ mapping_params['do_control'], mapping_params['control_marker'],
+ mapping_params['manhattan_plot'], None)
+
+ if mapping_params.get('limit_to'):
+ result_markers = result_markers[:mapping_params['limit_to']]
+
+ if mapping_params.get('format') == "csv":
+ output_rows = []
+ output_rows.append(header_row)
+ for marker in result_markers:
+ this_row = [marker[header] for header in header_row]
+ output_rows.append(this_row)
+
+ return output_rows, mapping_params['format']
+ elif mapping_params['format'] == "json":
+ return result_markers, mapping_params['format']
+ else:
+ return result_markers, None
+
+
+def initialize_parameters(start_vars, dataset, this_trait):
+ mapping_params = {}
+
+ mapping_params['format'] = "json"
+ if 'format' in start_vars:
+ mapping_params['format'] = start_vars['format']
+
+ mapping_params['limit_to'] = False
+ if 'limit_to' in start_vars:
+ if start_vars['limit_to'].isdigit():
+ mapping_params['limit_to'] = int(start_vars['limit_to'])
+
+ mapping_params['mapping_method'] = "gemma"
+ if 'method' in start_vars:
+ mapping_params['mapping_method'] = start_vars['method']
+
+ if mapping_params['mapping_method'] == "rqtl":
+ mapping_params['rqtl_method'] = "hk"
+ mapping_params['rqtl_model'] = "normal"
+ mapping_params['do_control'] = False
+ mapping_params['control_marker'] = ""
+ mapping_params['manhattan_plot'] = True
+ mapping_params['pair_scan'] = False
+ if 'rqtl_method' in start_vars:
+ mapping_params['rqtl_method'] = start_vars['rqtl_method']
+ if 'rqtl_model' in start_vars:
+ mapping_params['rqtl_model'] = start_vars['rqtl_model']
+ if 'control_marker' in start_vars:
+ mapping_params['control_marker'] = start_vars['control_marker']
+ mapping_params['do_control'] = True
+ if 'pair_scan' in start_vars:
+ if start_vars['pair_scan'].lower() == "true":
+ mapping_params['pair_scan'] = True
+
+ if 'interval_mapping' in start_vars:
+ if start_vars['interval_mapping'].lower() == "true":
+ mapping_params['manhattan_plot'] = False
+ elif 'manhattan_plot' in start_vars:
+ if start_vars['manhattan_plot'].lower() != "true":
+ mapping_params['manhattan_plot'] = False
+
+ mapping_params['maf'] = 0.01
+ if 'maf' in start_vars:
+ mapping_params['maf'] = start_vars['maf'] # Minor allele frequency
+
+ mapping_params['use_loco'] = True
+ if 'use_loco' in start_vars:
+ if (start_vars['use_loco'].lower() == "false") or (start_vars['use_loco'].lower() == "no"):
+ mapping_params['use_loco'] = False
+
+ mapping_params['num_perm'] = 0
+ mapping_params['perm_check'] = False
+ if 'num_perm' in start_vars:
+ try:
+ mapping_params['num_perm'] = int(start_vars['num_perm'])
+ mapping_params['perm_check'] = "ON"
+ except:
+ mapping_params['perm_check'] = False
+
+ mapping_params['transform'] = False
+ if 'transform' in start_vars:
+ mapping_params['transform'] = start_vars['transform']
+
+ mapping_params['genofile'] = False
+ if 'genofile' in start_vars:
+ mapping_params['genofile'] = start_vars['genofile']
+
+ return mapping_params
+
+def get_genofile_samplelist(dataset):
+ genofile_samplelist = []
+
+ genofile_json = dataset.group.get_genofiles()
+ for genofile in genofile_json:
+ if genofile['location'] == dataset.group.genofile and 'sample_list' in genofile:
+ genofile_samplelist = genofile['sample_list']
+
+ return genofile_samplelist
diff --git a/gn2/wqflask/api/markdown.py b/gn2/wqflask/api/markdown.py
new file mode 100644
index 00000000..580b9ac0
--- /dev/null
+++ b/gn2/wqflask/api/markdown.py
@@ -0,0 +1,186 @@
+"""Markdown routes
+
+Render pages from github, or if they are unavailable, look for it else where
+"""
+
+import requests
+import markdown
+import os
+import sys
+
+from bs4 import BeautifulSoup # type: ignore
+
+from flask import send_from_directory
+from flask import Blueprint
+from flask import render_template
+
+from typing import Dict
+from typing import List
+
+glossary_blueprint = Blueprint('glossary_blueprint', __name__)
+references_blueprint = Blueprint("references_blueprint", __name__)
+environments_blueprint = Blueprint("environments_blueprint", __name__)
+links_blueprint = Blueprint("links_blueprint", __name__)
+policies_blueprint = Blueprint("policies_blueprint", __name__)
+facilities_blueprint = Blueprint("facilities_blueprint", __name__)
+news_blueprint = Blueprint("news_blueprint", __name__)
+
+blogs_blueprint = Blueprint("blogs_blueprint", __name__)
+
+
+def render_markdown(file_name, is_remote_file=True):
+ """Try to fetch the file name from Github and if that fails, try to
+look for it inside the file system """
+ github_url = ("https://raw.githubusercontent.com/"
+ "genenetwork/gn-docs/master/")
+
+ if not is_remote_file:
+ text = ""
+ with open(file_name, "r", encoding="utf-8") as input_file:
+ text = input_file.read()
+ return markdown.markdown(text,
+ extensions=['tables'])
+
+ md_content = requests.get(f"{github_url}{file_name}")
+
+ if md_content.status_code == 200:
+ return markdown.markdown(md_content.content.decode("utf-8"),
+ extensions=['tables'])
+
+ return (f"\nContent for {file_name} not available. "
+ "Please check "
+ "(here to see where content exists)"
+ "[https://github.com/genenetwork/gn-docs]. "
+ "Please reach out to the gn2 team to have a look at this")
+
+
+def get_file_from_python_search_path(pathname_suffix):
+ cands = [os.path.join(d, pathname_suffix) for d in sys.path]
+ try:
+ return list(filter(os.path.exists, cands))[0]
+ except IndexError:
+ return None
+
+
+def get_blogs(user: str = "genenetwork",
+ repo_name: str = "gn-docs") -> dict:
+
+ blogs: Dict[int, List] = {}
+ github_url = f"https://api.github.com/repos/{user}/{repo_name}/git/trees/master?recursive=1"
+
+ repo_tree = requests.get(github_url).json()["tree"]
+
+ for data in repo_tree:
+ path_name = data["path"]
+ if path_name.startswith("blog") and path_name.endswith(".md"):
+ split_path = path_name.split("/")[1:]
+ try:
+ year, title, file_name = split_path
+ except Exception as e:
+ year, file_name = split_path
+ title = ""
+
+ subtitle = os.path.splitext(file_name)[0]
+
+ blog = {
+ "title": title,
+ "subtitle": subtitle,
+ "full_path": path_name
+ }
+
+ if year in blogs:
+ blogs[int(year)].append(blog)
+ else:
+ blogs[int(year)] = [blog]
+
+ return dict(sorted(blogs.items(), key=lambda x: x[0], reverse=True))
+
+
+@glossary_blueprint.route('/')
+def glossary():
+ return render_template(
+ "glossary.html",
+ rendered_markdown=render_markdown("general/glossary/glossary.md")), 200
+
+
+@references_blueprint.route('/')
+def references():
+ return render_template(
+ "references.html",
+ rendered_markdown=render_markdown("general/references/references.md")), 200
+
+
+@news_blueprint.route('/')
+def news():
+ return render_template(
+ "news.html",
+ rendered_markdown=render_markdown("general/news/news.md")), 200
+
+
+@environments_blueprint.route("/")
+def environments():
+
+ md_file = get_file_from_python_search_path("wqflask/DEPENDENCIES.md")
+ svg_file = get_file_from_python_search_path(
+ "wqflask/dependency-graph.html")
+ svg_data = None
+ if svg_file:
+ with open(svg_file, 'r') as f:
+ svg_data = "".join(
+ BeautifulSoup(f.read(),
+ 'lxml').body.script.contents)
+
+ if md_file is not None:
+ return (
+ render_template("environment.html",
+ svg_data=svg_data,
+ rendered_markdown=render_markdown(
+ md_file,
+ is_remote_file=False)),
+ 200
+ )
+ # Fallback: Fetch file from server
+ return (render_template(
+ "environment.html",
+ svg_data=None,
+ rendered_markdown=render_markdown(
+ "general/environments/environments.md")),
+ 200)
+
+
+@environments_blueprint.route('/svg-dependency-graph')
+def svg_graph():
+ directory, file_name, _ = get_file_from_python_search_path(
+ "wqflask/dependency-graph.svg").partition("dependency-graph.svg")
+ return send_from_directory(directory, file_name)
+
+
+@links_blueprint.route("/")
+def links():
+ return render_template(
+ "links.html",
+ rendered_markdown=render_markdown("general/links/links.md")), 200
+
+
+@policies_blueprint.route("/")
+def policies():
+ return render_template(
+ "policies.html",
+ rendered_markdown=render_markdown("general/policies/policies.md")), 200
+
+
+@facilities_blueprint.route("/")
+def facilities():
+ return render_template("facilities.html", rendered_markdown=render_markdown("general/help/facilities.md")), 200
+
+
+@blogs_blueprint.route("/<path:blog_path>")
+def display_blog(blog_path):
+ return render_template("blogs.html", rendered_markdown=render_markdown(blog_path))
+
+
+@blogs_blueprint.route("/")
+def blogs_list():
+ blogs = get_blogs()
+
+ return render_template("blogs_list.html", blogs=blogs)
diff --git a/gn2/wqflask/api/router.py b/gn2/wqflask/api/router.py
new file mode 100644
index 00000000..bcd08e8d
--- /dev/null
+++ b/gn2/wqflask/api/router.py
@@ -0,0 +1,1037 @@
+# GN2 API
+
+import os
+import io
+import csv
+import json
+import datetime
+import requests
+
+from zipfile import ZipFile, ZIP_DEFLATED
+
+
+import flask
+from flask import current_app
+from gn2.wqflask.database import database_connection
+from flask import request
+from flask import make_response
+from flask import send_file
+
+from gn2.wqflask import app
+
+from gn2.wqflask.api import correlation, mapping, gen_menu
+
+from gn2.utility.tools import flat_files, get_setting
+
+from gn2.wqflask.database import database_connection
+
+
+version = "pre1"
+
+
+@app.route("/api/v_{}/".format(version))
+def hello_world():
+ return flask.jsonify({"hello": "world"})
+
+
+@app.route("/api/v_{}/species".format(version))
+def get_species_list():
+ species_list = []
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT SpeciesId, Name, FullName, TaxonomyId FROM Species"
+ )
+ for species in cursor.fetchall():
+ species_dict = {
+ "Id": species[0],
+ "Name": species[1],
+ "FullName": species[2],
+ "TaxonomyId": species[3]
+ }
+ species_list.append(species_dict)
+ return flask.jsonify(species_list)
+
+
+@app.route("/api/v_{}/species/<path:species_name>".format(version))
+@app.route("/api/v_{}/species/<path:species_name>.<path:file_format>".format(version))
+def get_species_info(species_name, file_format="json"):
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT SpeciesId, Name, FullName, TaxonomyId "
+ "FROM Species WHERE (Name=%s OR FullName=%s "
+ "OR SpeciesName=%s)", ((species_name,)*3))
+ _species = cursor.fetchone()
+ species_dict = {
+ "Id": _species[0],
+ "Name": _species[1],
+ "FullName": _species[2],
+ "TaxonomyId": _species[3]
+ }
+
+ return flask.jsonify(species_dict)
+
+
+@app.route("/api/v_{}/groups".format(version))
+@app.route("/api/v_{}/groups/<path:species_name>".format(version))
+def get_groups_list(species_name=None):
+ _groups = ()
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ if species_name:
+ cursor.execute(
+ "SELECT InbredSet.InbredSetId, "
+ "InbredSet.SpeciesId, InbredSet.InbredSetName, "
+ "InbredSet.Name, InbredSet.FullName, "
+ "InbredSet.public, IFNULL(InbredSet.MappingMethodId, "
+ "'None'), IFNULL(InbredSet.GeneticType, 'None') "
+ "FROM InbredSet, Species WHERE "
+ "InbredSet.SpeciesId = Species.Id AND "
+ "(Species.Name = %s OR Species.FullName=%s "
+ "OR Species.SpeciesName=%s)", ((species_name,) * 3)
+ )
+ else:
+ cursor.execute(
+ "SELECT InbredSet.InbredSetId, "
+ "InbredSet.SpeciesId, InbredSet.InbredSetName, "
+ "InbredSet.Name, InbredSet.FullName, "
+ "InbredSet.public, IFNULL(InbredSet.MappingMethodId, "
+ "'None'), IFNULL(InbredSet.GeneticType, 'None') "
+ "FROM InbredSet"
+ )
+ _groups = cursor.fetchall()
+
+ if _groups:
+ groups_list = []
+ for group in _groups:
+ group_dict = {
+ "Id": group[0],
+ "SpeciesId": group[1],
+ "DisplayName": group[2],
+ "Name": group[3],
+ "FullName": group[4],
+ "public": group[5],
+ "MappingMethodId": group[6],
+ "GeneticType": group[7]
+ }
+ groups_list.append(group_dict)
+ return flask.jsonify(groups_list)
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/group/<path:group_name>".format(version))
+@app.route("/api/v_{}/group/<path:group_name>.<path:file_format>".format(version))
+@app.route("/api/v_{}/group/<path:species_name>/<path:group_name>".format(version))
+@app.route("/api/v_{}/group/<path:species_name>/<path:group_name>.<path:file_format>".format(version))
+def get_group_info(group_name, species_name=None, file_format="json"):
+ group = tuple()
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ if species_name:
+ cursor.execute(
+ "SELECT InbredSet.InbredSetId, InbredSet.SpeciesId, "
+ "InbredSet.InbredSetName, InbredSet.Name, "
+ "InbredSet.FullName, InbredSet.public, "
+ "IFNULL(InbredSet.MappingMethodId, 'None'), "
+ "IFNULL(InbredSet.GeneticType, 'None') "
+ "FROM InbredSet, Species WHERE "
+ "InbredSet.SpeciesId = Species.Id "
+ "AND (InbredSet.InbredSetName = %s OR "
+ "InbredSet.Name = %s OR InbredSet.FullName = %s) "
+ "AND (Species.Name = %s OR "
+ "Species.FullName = %s OR Species.SpeciesName = %s)",
+ (*(group_name,)*3, *(species_name,)*3)
+ )
+ else:
+ cursor.execute(
+ "SELECT InbredSet.InbredSetId, InbredSet.SpeciesId, "
+ "InbredSet.InbredSetName, InbredSet.Name, "
+ "InbredSet.FullName, InbredSet.public, "
+ "IFNULL(InbredSet.MappingMethodId, 'None'), "
+ "IFNULL(InbredSet.GeneticType, 'None') "
+ "FROM InbredSet WHERE "
+ "(InbredSet.InbredSetName = %s OR "
+ "InbredSet.Name = %s OR "
+ "InbredSet.FullName = %s)",
+ ((group_name,)*3)
+ )
+ group = cursor.fetchone()
+
+ if group:
+ group_dict = {
+ "Id": group[0],
+ "SpeciesId": group[1],
+ "DisplayName": group[2],
+ "Name": group[3],
+ "FullName": group[4],
+ "public": group[5],
+ "MappingMethodId": group[6],
+ "GeneticType": group[7]
+ }
+
+ return flask.jsonify(group_dict)
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/datasets/<path:group_name>".format(version))
+@app.route("/api/v_{}/datasets/<path:species_name>/<path:group_name>".format(version))
+def get_datasets_for_group(group_name, species_name=None):
+ _datasets = ()
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ if species_name:
+ cursor.execute(
+ "SELECT ProbeSetFreeze.Id, ProbeSetFreeze.ProbeFreezeId, "
+ "ProbeSetFreeze.AvgID, ProbeSetFreeze.Name, "
+ "ProbeSetFreeze.Name2, "
+ "ProbeSetFreeze.FullName, ProbeSetFreeze.ShortName, "
+ "ProbeSetFreeze.CreateTime, ProbeSetFreeze.public, "
+ "ProbeSetFreeze.confidentiality, ProbeSetFreeze.DataScale "
+ "FROM ProbeSetFreeze, ProbeFreeze, InbredSet, Species "
+ "WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id "
+ "AND ProbeFreeze.InbredSetId = InbredSet.Id "
+ "AND (InbredSet.Name = %s OR "
+ "InbredSet.InbredSetName = %s OR "
+ "InbredSet.FullName = %s) AND "
+ "InbredSet.SpeciesId = Species.Id AND "
+ "(Species.SpeciesName = %s OR "
+ "Species.MenuName = %s OR Species.FullName = %s);",
+ (*(group_name,)*3, *(species_name)*3)
+ )
+ else:
+ cursor.execute(
+ "SELECT ProbeSetFreeze.Id, ProbeSetFreeze.ProbeFreezeId, "
+ "ProbeSetFreeze.AvgID, ProbeSetFreeze.Name, "
+ "ProbeSetFreeze.Name2, ProbeSetFreeze.FullName, "
+ "ProbeSetFreeze.ShortName, ProbeSetFreeze.CreateTime, "
+ "ProbeSetFreeze.public, ProbeSetFreeze.confidentiality, "
+ "ProbeSetFreeze.DataScale FROM ProbeSetFreeze, "
+ "ProbeFreeze, InbredSet WHERE "
+ "ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id "
+ "AND ProbeFreeze.InbredSetId = InbredSet.Id "
+ "AND (InbredSet.Name = %s OR "
+ "InbredSet.InbredSetName = %s OR "
+ "InbredSet.FullName = %s)",
+ ((group_name,) * 3)
+ )
+ _datasets = cursor.fetchall()
+
+ if _datasets:
+ datasets_list = []
+ for dataset in _datasets:
+ dataset_dict = {
+ "Id": dataset[0],
+ "ProbeFreezeId": dataset[1],
+ "AvgID": dataset[2],
+ "Short_Abbreviation": dataset[3],
+ "Long_Abbreviation": dataset[4],
+ "FullName": dataset[5],
+ "ShortName": dataset[6],
+ "CreateTime": dataset[7],
+ "public": dataset[8],
+ "confidentiality": dataset[9],
+ "DataScale": dataset[10]
+ }
+ datasets_list.append(dataset_dict)
+
+ return flask.jsonify(datasets_list)
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/dataset/<path:dataset_name>".format(version))
+@app.route("/api/v_{}/dataset/<path:dataset_name>.<path:file_format>".format(version))
+@app.route("/api/v_{}/dataset/<path:group_name>/<path:dataset_name>".format(version))
+@app.route("/api/v_{}/dataset/<path:group_name>/<path:dataset_name>.<path:file_format>".format(version))
+def get_dataset_info(dataset_name, group_name=None, file_format="json"):
+ # ZS: First get ProbeSet (mRNA expression) datasets and then get Phenotype datasets
+
+ # ZS: I figure I might as well return a list if there are multiple
+ # matches, though I don"t know if this will actually happen in
+ # practice
+ datasets_list, dataset_dict = [], {}
+ probeset_query = """
+ SELECT ProbeSetFreeze.Id, ProbeSetFreeze.Name, ProbeSetFreeze.FullName,
+ ProbeSetFreeze.ShortName, ProbeSetFreeze.DataScale, ProbeFreeze.TissueId,
+ Tissue.Name, ProbeSetFreeze.public, ProbeSetFreeze.confidentiality
+ FROM ProbeSetFreeze, ProbeFreeze, Tissue
+ """
+
+ where_statement = """
+ WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id AND
+ ProbeFreeze.TissueId = Tissue.Id AND
+ ProbeSetFreeze.public > 0 AND
+ ProbeSetFreeze.confidentiality < 1 AND
+ """
+ if dataset_name.isdigit():
+ where_statement += """
+ ProbeSetFreeze.Id = "{}"
+ """.format(dataset_name)
+ else:
+ where_statement += """
+ (ProbeSetFreeze.Name = "{0}" OR ProbeSetFreeze.Name2 = "{0}" OR
+ ProbeSetFreeze.FullName = "{0}" OR ProbeSetFreeze.ShortName = "{0}")
+ """.format(dataset_name)
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ cursor.execute(f"{probeset_query}{where_statement}")
+
+ if dataset := cursor.fetchone():
+ dataset_dict = {
+ "dataset_type": "mRNA expression",
+ "id": dataset[0],
+ "name": dataset[1],
+ "full_name": dataset[2],
+ "short_name": dataset[3],
+ "data_scale": dataset[4],
+ "tissue_id": dataset[5],
+ "tissue": dataset[6],
+ "public": dataset[7],
+ "confidential": dataset[8]
+ }
+
+ datasets_list.append(dataset_dict)
+
+ if group_name:
+ cursor.execute(
+ "SELECT PublishXRef.Id, "
+ "Phenotype.Post_publication_abbreviation, "
+ "Phenotype.Post_publication_description, "
+ "Phenotype.Pre_publication_abbreviation, "
+ "Phenotype.Pre_publication_description, "
+ "Publication.PubMed_ID, Publication.Title, "
+ "Publication.Year FROM PublishXRef, Phenotype, "
+ "Publication, InbredSet, PublishFreeze WHERE "
+ "PublishXRef.InbredSetId = InbredSet.Id "
+ "AND PublishXRef.PhenotypeId = Phenotype.Id "
+ "AND PublishXRef.PublicationId = Publication.Id "
+ "AND PublishFreeze.InbredSetId = InbredSet.Id "
+ "AND PublishFreeze.public > 0 AND "
+ "PublishFreeze.confidentiality < 1 "
+ "AND InbredSet.Name = %s AND PublishXRef.Id = %s",
+ (group_name, dataset_name,)
+ )
+
+ if dataset := cursor.fetchone():
+ if dataset[5]:
+ dataset_dict = {
+ "dataset_type": "phenotype",
+ "id": dataset[0],
+ "name": dataset[1],
+ "description": dataset[2],
+ "pubmed_id": dataset[5],
+ "title": dataset[6],
+ "year": dataset[7]
+ }
+ elif dataset[4]:
+ dataset_dict = {
+ "dataset_type": "phenotype",
+ "id": dataset[0],
+ "name": dataset[3],
+ "description": dataset[4]
+ }
+ else:
+ dataset_dict = {
+ "dataset_type": "phenotype",
+ "id": dataset[0]
+ }
+
+ datasets_list.append(dataset_dict)
+
+ if len(datasets_list) > 1:
+ return flask.jsonify(datasets_list)
+ elif len(datasets_list) == 1:
+ return flask.jsonify(dataset_dict)
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/traits/<path:dataset_name>".format(version), methods=("GET",))
+@app.route("/api/v_{}/traits/<path:dataset_name>.<path:file_format>".format(version), methods=("GET",))
+def fetch_traits(dataset_name, file_format="json"):
+ trait_ids, trait_names, data_type, dataset_id = get_dataset_trait_ids(
+ dataset_name, request.args)
+ if ("ids_only" in request.args) and (len(trait_ids) > 0):
+ if file_format == "json":
+ filename = dataset_name + "_trait_ids.json"
+ return flask.jsonify(trait_ids)
+ else:
+ filename = dataset_name + "_trait_ids.csv"
+
+ si = io.StringIO()
+ csv_writer = csv.writer(si)
+ csv_writer.writerows([[trait_id] for trait_id in trait_ids])
+ output = make_response(si.getvalue())
+ output.headers["Content-Disposition"] = "attachment; filename=" + filename
+ output.headers["Content-type"] = "text/csv"
+ return output
+ elif ("names_only" in request.args) and (len(trait_ids) > 0):
+ if file_format == "json":
+ filename = dataset_name + "_trait_names.json"
+ return flask.jsonify(trait_names)
+ else:
+ filename = dataset_name + "_trait_names.csv"
+
+ si = io.StringIO()
+ csv_writer = csv.writer(si)
+ csv_writer.writerows([[trait_name] for trait_name in trait_names])
+ output = make_response(si.getvalue())
+ output.headers["Content-Disposition"] = "attachment; filename=" + filename
+ output.headers["Content-type"] = "text/csv"
+ return output
+ else:
+ if len(trait_ids) > 0:
+ if data_type == "ProbeSet":
+ query = """
+ SELECT
+ ProbeSet.Id, ProbeSet.Name, ProbeSet.Symbol, ProbeSet.description, ProbeSet.Chr, ProbeSet.Mb, ProbeSet.alias,
+ ProbeSetXRef.mean, ProbeSetXRef.se, ProbeSetXRef.Locus, ProbeSetXRef.LRS, ProbeSetXRef.pValue, ProbeSetXRef.additive, ProbeSetXRef.h2
+ FROM
+ ProbeSet, ProbeSetXRef, ProbeSetFreeze
+ WHERE
+ ProbeSetXRef.ProbeSetFreezeId = "{0}" AND
+ ProbeSetXRef.ProbeSetId = ProbeSet.Id AND
+ ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND
+ ProbeSetFreeze.public > 0 AND
+ ProbeSetFreeze.confidentiality < 1
+ ORDER BY
+ ProbeSet.Id
+ """
+
+ field_list = ["Id", "Name", "Symbol", "Description", "Chr", "Mb",
+ "Aliases", "Mean", "SE", "Locus", "LRS", "P-Value", "Additive", "h2"]
+ elif data_type == "Geno":
+ query = """
+ SELECT
+ Geno.Id, Geno.Name, Geno.Marker_Name, Geno.Chr, Geno.Mb, Geno.Sequence, Geno.Source
+ FROM
+ Geno, GenoXRef, GenoFreeze
+ WHERE
+ GenoXRef.GenoFreezeId = "{0}" AND
+ GenoXRef.GenoId = Geno.Id AND
+ GenoXRef.GenoFreezeId = GenoFreeze.Id AND
+ GenoFreeze.public > 0 AND
+ GenoFreeze.confidentiality < 1
+ ORDER BY
+ Geno.Id
+ """
+
+ field_list = ["Id", "Name", "Marker_Name",
+ "Chr", "Mb", "Sequence", "Source"]
+ else:
+ query = """SELECT PublishXRef.Id,
+ Phenotype.`Original_description`,
+ Publication.`Authors`,
+ Publication.`Year`,
+ Publication.`PubMed_ID`,
+ PublishXRef.`mean`,
+ PublishXRef.`LRS`,
+ PublishXRef.`additive`,
+ PublishXRef.`Locus`,
+ Geno.`Chr`, Geno.`Mb`
+ FROM Species
+ INNER JOIN InbredSet ON InbredSet.`SpeciesId` = Species.`Id`
+ INNER JOIN PublishXRef ON PublishXRef.`InbredSetId` = InbredSet.`Id`
+ INNER JOIN PublishFreeze ON PublishFreeze.`InbredSetId` = InbredSet.`Id`
+ INNER JOIN Publication ON Publication.`Id` = PublishXRef.`PublicationId`
+ INNER JOIN Phenotype ON Phenotype.`Id` = PublishXRef.`PhenotypeId`
+ LEFT JOIN Geno ON PublishXRef.Locus = Geno.Name AND Geno.SpeciesId = Species.Id
+ WHERE
+ PublishXRef.InbredSetId = {0} AND
+ PublishFreeze.InbredSetId = PublishXRef.InbredSetId AND
+ PublishFreeze.public > 0 AND
+ PublishFreeze.confidentiality < 1
+ ORDER BY
+ PublishXRef.Id"""
+
+ field_list = ["Id", "Description", "Authors", "Year", "PubMedID", "Mean",
+ "LRS", "Additive", "Locus", "Chr", "Mb"]
+
+ if 'limit_to' in request.args:
+ limit_number = request.args['limit_to']
+ query += "LIMIT " + str(limit_number)
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ if file_format == "json":
+ filename = dataset_name + "_traits.json"
+ cursor.execute(query.format(dataset_id))
+ result_list = []
+ for result in cursor.fetchall():
+ trait_dict = {}
+ for i, field in enumerate(field_list):
+ if result[i]:
+ trait_dict[field] = result[i]
+ result_list.append(trait_dict)
+ return flask.jsonify(result_list)
+ elif file_format == "csv":
+ filename = dataset_name + "_traits.csv"
+
+ results_list = []
+ header_list = []
+ header_list += field_list
+ results_list.append(header_list)
+ cursor.execute(query.format(dataset_id))
+ for result in cursor.fetchall():
+ results_list.append(result)
+
+ si = io.StringIO()
+ csv_writer = csv.writer(si)
+ csv_writer.writerows(results_list)
+ output = make_response(si.getvalue())
+ output.headers["Content-Disposition"] = "attachment; filename=" + filename
+ output.headers["Content-type"] = "text/csv"
+ return output
+ else:
+ return return_error(
+ code=400,
+ source=request.url_rule.rule,
+ title="Invalid Output Format",
+ details="Current formats available are JSON and CSV, with CSV as default"
+ )
+ else:
+ return return_error(
+ code=204,
+ source=request.url_rule.rule,
+ title="No Results",
+ details="")
+
+
+@app.route("/api/v_{}/sample_data/<path:dataset_name>".format(version))
+@app.route("/api/v_{}/sample_data/<path:dataset_name>.<path:file_format>".format(version))
+def all_sample_data(dataset_name, file_format="csv"):
+ trait_ids, trait_names, data_type, dataset_id = get_dataset_trait_ids(
+ dataset_name, request.args)
+
+ if len(trait_ids) > 0:
+ sample_list = get_samplelist(dataset_name)
+
+ if data_type == "ProbeSet":
+ query = """
+ SELECT
+ Strain.Name, Strain.Name2, ProbeSetData.value, ProbeSetData.Id, ProbeSetSE.error
+ FROM
+ (ProbeSetData, Strain, ProbeSetXRef, ProbeSetFreeze)
+ LEFT JOIN ProbeSetSE ON
+ (ProbeSetSE.DataId = ProbeSetData.Id AND ProbeSetSE.StrainId = ProbeSetData.StrainId)
+ WHERE
+ ProbeSetXRef.ProbeSetFreezeId = "{0}" AND
+ ProbeSetXRef.ProbeSetId = "{1}" AND
+ ProbeSetXRef.DataId = ProbeSetData.Id AND
+ ProbeSetData.StrainId = Strain.Id AND
+ ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND
+ ProbeSetFreeze.public > 0 AND
+ ProbeSetFreeze.confidentiality < 1
+ ORDER BY
+ Strain.Name
+ """
+ elif data_type == "Geno":
+ query = """
+ SELECT
+ Strain.Name, Strain.Name2, GenoData.value, GenoData.Id, GenoSE.error
+ FROM
+ (GenoData, Strain, GenoXRef, GenoFreeze)
+ LEFT JOIN GenoSE ON
+ (GenoSE.DataId = GenoData.Id AND GenoSE.StrainId = GenoData.StrainId)
+ WHERE
+ GenoXRef.GenoFreezeId = "{0}" AND
+ GenoXRef.GenoId = "{1}" AND
+ GenoXRef.DataId = GenoData.Id AND
+ GenoData.StrainId = Strain.Id AND
+ GenoXRef.GenoFreezeId = GenoFreeze.Id AND
+ GenoFreeze.public > 0 AND
+ GenoFreeze.confidentiality < 1
+ ORDER BY
+ Strain.Name
+ """
+ else:
+ query = """
+ SELECT
+ Strain.Name, Strain.Name2, PublishData.value, PublishData.Id, PublishSE.error, NStrain.count
+ 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 = "{0}" AND
+ PublishXRef.PhenotypeId = "{1}" AND
+ PublishData.Id = PublishXRef.DataId AND
+ PublishData.StrainId = Strain.Id AND
+ PublishXRef.InbredSetId = PublishFreeze.InbredSetId AND
+ PublishFreeze.public > 0 AND
+ PublishFreeze.confidentiality < 1
+ ORDER BY
+ Strain.Name
+ """
+
+ if file_format == "csv":
+ filename = dataset_name + "_sample_data.csv"
+
+ results_list = []
+ header_list = []
+ header_list.append("id")
+ header_list += sample_list
+ results_list.append(header_list)
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ for i, trait_id in enumerate(trait_ids):
+ line_list = []
+ line_list.append(str(trait_names[i]))
+ cursor.execute(query.format(dataset_id, trait_id))
+ results = cursor.fetchall()
+ results_dict = {}
+ for item in results:
+ results_dict[item[0]] = item[2]
+ for sample in sample_list:
+ if sample in results_dict:
+ line_list.append(results_dict[sample])
+ else:
+ line_list.append("x")
+ results_list.append(line_list)
+
+ results_list = list(map(list, zip(*results_list)))
+
+ si = io.StringIO()
+ csv_writer = csv.writer(si)
+ csv_writer.writerows(results_list)
+ output = make_response(si.getvalue())
+ output.headers["Content-Disposition"] = "attachment; filename=" + filename
+ output.headers["Content-type"] = "text/csv"
+ return output
+ else:
+ return return_error(code=415, source=request.url_rule.rule, title="Unsupported file format", details="")
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/sample_data/<path:dataset_name>/<path:trait_name>".format(version))
+@app.route("/api/v_{}/sample_data/<path:dataset_name>/<path:trait_name>.<path:file_format>".format(version))
+def trait_sample_data(dataset_name, trait_name, file_format="json"):
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT Strain.Name, Strain.Name2, "
+ "ProbeSetData.value, ProbeSetData.Id, "
+ "ProbeSetSE.error 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",
+ (trait_name, dataset_name,)
+ )
+
+ sample_data = cursor.fetchall()
+ if len(sample_data) > 0:
+ sample_list = []
+ for sample in sample_data:
+ sample_dict = {
+ "sample_name": sample[0],
+ "sample_name_2": sample[1],
+ "value": sample[2],
+ "data_id": sample[3],
+ }
+ if sample[4]:
+ sample_dict["se"] = sample[4]
+ sample_list.append(sample_dict)
+
+ return flask.jsonify(sample_list)
+ else:
+ if not dataset_name.isdigit():
+ group_id = get_group_id(dataset_name)
+ if group_id:
+ dataset_or_group = group_id
+ else:
+ dataset_or_group = dataset_name
+ else:
+ dataset_or_group = dataset_name
+
+ cursor.execute(
+ "SELECT DISTINCT Strain.Name, Strain.Name2, "
+ "PublishData.value, PublishData.Id, PublishSE.error, "
+ "NStrain.count 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 "
+ "OR PublishFreeze.Name = %s OR "
+ "PublishFreeze.ShortName = %s OR "
+ "PublishXRef.InbredSetId = %s) AND "
+ "PublishData.StrainId = Strain.Id "
+ "ORDER BY Strain.Name",
+ (trait_name, *(dataset_or_group,)*4)
+ )
+ if len(sample_data := cursor.fetchall()) > 0:
+ sample_list = []
+ for sample in sample_data:
+ sample_dict = {
+ "sample_name": sample[0],
+ "sample_name_2": sample[1],
+ "value": sample[2],
+ "data_id": sample[3]
+ }
+ if sample[4]:
+ sample_dict["se"] = sample[4]
+ if sample[5]:
+ sample_dict["n_cases"] = sample[5]
+ sample_list.append(sample_dict)
+
+ return flask.jsonify(sample_list)
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/trait/<path:dataset_name>/<path:trait_name>".format(version))
+@app.route("/api/v_{}/trait/<path:dataset_name>/<path:trait_name>.<path:file_format>".format(version))
+@app.route("/api/v_{}/trait_info/<path:dataset_name>/<path:trait_name>".format(version))
+@app.route("/api/v_{}/trait_info/<path:dataset_name>/<path:trait_name>.<path:file_format>".format(version))
+def get_trait_info(dataset_name, trait_name, file_format="json"):
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT ProbeSet.Id, ProbeSet.Name, ProbeSet.Symbol, "
+ "ProbeSet.description, ProbeSet.Chr, ProbeSet.Mb, "
+ "ProbeSet.alias, ProbeSetXRef.mean, ProbeSetXRef.se, "
+ "ProbeSetXRef.Locus, ProbeSetXRef.LRS, "
+ "ProbeSetXRef.pValue, ProbeSetXRef.additive "
+ "FROM ProbeSet, ProbeSetXRef, ProbeSetFreeze "
+ "WHERE ProbeSet.Name = %s AND "
+ "ProbeSetXRef.ProbeSetId = ProbeSet.Id AND "
+ "ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id "
+ "AND ProbeSetFreeze.Name = %s",
+ (trait_name, dataset_name,)
+ )
+ if trait_info := cursor.fetchone():
+ trait_dict = {
+ "id": trait_info[0],
+ "name": trait_info[1],
+ "symbol": trait_info[2],
+ "description": trait_info[3],
+ "chr": trait_info[4],
+ "mb": trait_info[5],
+ "alias": trait_info[6],
+ "mean": trait_info[7],
+ "se": trait_info[8],
+ "locus": trait_info[9],
+ "lrs": trait_info[10],
+ "p_value": trait_info[11],
+ "additive": trait_info[12]
+ }
+
+ return flask.jsonify(trait_dict)
+ else:
+ # ZS: Check if the user input the dataset_name as BXDPublish, etc (which is always going to be the group name + "Publish"
+ if "Publish" in dataset_name:
+ dataset_name = dataset_name.replace("Publish", "")
+
+ group_id = get_group_id(dataset_name)
+ cursor.execute(
+ "SELECT PublishXRef.PhenotypeId, "
+ "PublishXRef.Locus, PublishXRef.LRS, "
+ "PublishXRef.additive FROM "
+ "PublishXRef WHERE "
+ "PublishXRef.Id = %s AND "
+ "PublishXRef.InbredSetId = %s",
+ (trait_name, group_id,)
+ )
+ if trait_info := cursor.fetchone():
+ trait_dict = {
+ "id": trait_info[0],
+ "locus": trait_info[1],
+ "lrs": trait_info[2],
+ "additive": trait_info[3]
+ }
+
+ return flask.jsonify(trait_dict)
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/correlation".format(version), methods=("GET",))
+def get_corr_results():
+ results = correlation.do_correlation(request.args)
+
+ if len(results) > 0:
+ # ZS: I think flask.jsonify expects a dict/list instead of JSON
+ return flask.jsonify(results)
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/mapping".format(version), methods=("GET",))
+def get_mapping_results():
+ results, format = mapping.do_mapping_for_api(request.args)
+
+ if len(results) > 0:
+ if format == "csv":
+ filename = "mapping_" + datetime.datetime.utcnow().strftime("%b_%d_%Y_%I:%M%p") + ".csv"
+
+ si = io.StringIO()
+ csv_writer = csv.writer(si)
+ csv_writer.writerows(results)
+ output = make_response(si.getvalue())
+ output.headers["Content-Disposition"] = "attachment; filename=" + filename
+ output.headers["Content-type"] = "text/csv"
+
+ return output
+ elif format == "json":
+ return flask.jsonify(results)
+ else:
+ return return_error(code=415, source=request.url_rule.rule, title="Unsupported Format", details="")
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+
+@app.route("/api/v_{}/genotypes/view/<string:group_name>".format(version))
+def view_genotype_files(group_name):
+ if os.path.isfile("{0}/{1}.json".format(flat_files("genotype"), group_name)):
+ with open("{0}/{1}.json".format(flat_files("genotype"), group_name)) as geno_json:
+ return flask.jsonify(json.load(geno_json))
+
+
+@app.route("/api/v_{}/genotypes/<string:file_format>/<string:group_name>/<string:dataset_name>.zip".format(version))
+@app.route("/api/v_{}/genotypes/<string:file_format>/<string:group_name>/<string:dataset_name>".format(version))
+@app.route("/api/v_{}/genotypes/<string:file_format>/<string:group_name>.zip".format(version))
+@app.route("/api/v_{}/genotypes/<string:file_format>/<string:group_name>".format(version))
+@app.route("/api/v_{}/genotypes/<string:group_name>.<string:file_format>".format(version))
+def get_genotypes(group_name, file_format="csv", dataset_name=None):
+ limit_num = None
+ if 'limit_to' in request.args:
+ if request.args['limit_to'].isdigit():
+ limit_num = int(request.args['limit_to'])
+
+ si = io.StringIO()
+ if file_format == "csv" or file_format == "geno":
+ filename = group_name + ".geno"
+
+ if os.path.isfile("{0}/{1}.geno".format(flat_files("genotype"), group_name)):
+ output_lines = []
+ with open("{0}/{1}.geno".format(flat_files("genotype"), group_name)) as genofile:
+ i = 0
+ for line in genofile:
+ if line[0] == "#" or line[0] == "@":
+ output_lines.append([line.strip()])
+ else:
+ if limit_num and i >= limit_num:
+ break
+ output_lines.append(line.split())
+ i += 1
+
+ csv_writer = csv.writer(
+ si, delimiter="\t", escapechar="\\", quoting=csv.QUOTE_NONE)
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+ elif file_format == "rqtl2":
+ memory_file = io.BytesIO()
+ if dataset_name:
+ filename = dataset_name
+ else:
+ filename = group_name
+
+ if os.path.isfile("{0}/{1}_geno.csv".format(flat_files("genotype/rqtl2"), group_name)):
+ yaml_file = json.load(
+ open("{0}/{1}.json".format(flat_files("genotype/rqtl2"), group_name)))
+ yaml_file["geno"] = filename + "_geno.csv"
+ yaml_file["gmap"] = filename + "_gmap.csv"
+ yaml_file["pheno"] = filename + "_pheno.csv"
+ config_file = [filename + ".json", json.dumps(yaml_file)]
+ #config_file = [filename + ".yaml", open("{0}/{1}.yaml".format(flat_files("genotype/rqtl2"), group_name))]
+ geno_file = [filename + "_geno.csv",
+ open("{0}/{1}_geno.csv".format(flat_files("genotype/rqtl2"), group_name))]
+ gmap_file = [filename + "_gmap.csv",
+ open("{0}/{1}_gmap.csv".format(flat_files("genotype/rqtl2"), group_name))]
+ if dataset_name:
+ phenotypes = requests.get(
+ "http://gn2.genenetwork.org/api/v_pre1/sample_data/" + dataset_name)
+ else:
+ phenotypes = requests.get(
+ "http://gn2.genenetwork.org/api/v_pre1/sample_data/" + group_name + "Publish")
+
+ with ZipFile(memory_file, 'w', compression=ZIP_DEFLATED) as zf:
+ zf.writestr(config_file[0], config_file[1])
+ for this_file in [geno_file, gmap_file]:
+ zf.writestr(this_file[0], this_file[1].read())
+ zf.writestr(filename + "_pheno.csv", phenotypes.content)
+
+ memory_file.seek(0)
+
+ return send_file(memory_file, attachment_filename=filename + ".zip", as_attachment=True)
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+ else:
+ filename = group_name + ".bimbam"
+
+ if os.path.isfile("{0}/{1}.geno".format(flat_files("genotype"), group_name)):
+ output_lines = []
+ with open("{0}/{1}_geno.txt".format(flat_files("genotype/bimbam"), group_name)) as genofile:
+ i = 0
+ for line in genofile:
+ if limit_num and i >= limit_num:
+ break
+ output_lines.append([line.strip()
+ for line in line.split(",")])
+ i += 1
+
+ csv_writer = csv.writer(si, delimiter=",")
+ else:
+ return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+
+ csv_writer.writerows(output_lines)
+ output = make_response(si.getvalue())
+ output.headers["Content-Disposition"] = "attachment; filename=" + filename
+ output.headers["Content-type"] = "text/csv"
+
+ return output
+
+
+@app.route("/api/v_{}/gen_dropdown".format(version), methods=("GET",))
+def gen_dropdown_menu():
+ with database_connection(get_setting("SQL_URI")) as conn:
+ results = gen_menu.gen_dropdown_json(conn)
+
+ if len(results) > 0:
+ return flask.jsonify(results)
+ else:
+ return return_error(code=500, source=request.url_rule.rule, title="Some error occurred", details="")
+
+
+def return_error(code, source, title, details):
+ json_ob = {"errors": [
+ {
+ "status": code,
+ "source": {"pointer": source},
+ "title": title,
+ "detail": details
+ }
+ ]}
+
+ return flask.jsonify(json_ob)
+
+
+def get_dataset_trait_ids(dataset_name, start_vars):
+
+ if 'limit_to' in start_vars:
+ limit_string = "LIMIT " + str(start_vars['limit_to'])
+ else:
+ limit_string = ""
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ if "Geno" in dataset_name:
+ data_type = "Geno" # ZS: Need to pass back the dataset type
+ cursor.execute(
+ "SELECT GenoXRef.GenoId, Geno.Name, "
+ "GenoXRef.GenoFreezeId FROM Geno, "
+ "GenoXRef, GenoFreeze WHERE "
+ "Geno.Id = GenoXRef.GenoId AND "
+ "GenoXRef.GenoFreezeId = GenoFreeze.Id "
+ f"AND GenoFreeze.Name = %s {limit_string}",
+ (dataset_name,))
+
+ results = cursor.fetchall()
+
+ trait_ids = [result[0] for result in results]
+ trait_names = [result[1] for result in results]
+ dataset_id = results[0][2]
+ return trait_ids, trait_names, data_type, dataset_id
+
+ elif "Publish" in dataset_name or get_group_id(dataset_name):
+ data_type = "Publish"
+ dataset_name = dataset_name.replace("Publish", "")
+ dataset_id = get_group_id(dataset_name)
+ cursor.execute(
+ "SELECT PublishXRef.PhenotypeId, "
+ "PublishXRef.Id, InbredSet.InbredSetCode "
+ "FROM PublishXRef, InbredSet WHERE "
+ "PublishXRef.InbredSetId = %s AND "
+ "InbredSet.Id = PublishXRef.InbredSetId "
+ f"{limit_string}",
+ (dataset_id,)
+ )
+ results = cursor.fetchall()
+
+ trait_ids = [result[0] for result in results]
+ trait_names = [str(result[2]) + "_" + str(result[1])
+ for result in results]
+
+ return trait_ids, trait_names, data_type, dataset_id
+
+ else:
+ data_type = "ProbeSet"
+ cursor.execute(
+ "SELECT ProbeSetXRef.ProbeSetId, "
+ "ProbeSet.Name, ProbeSetXRef.ProbeSetFreezeId "
+ "FROM ProbeSet, ProbeSetXRef, "
+ "ProbeSetFreeze WHERE "
+ "ProbeSet.Id = ProbeSetXRef.ProbeSetId AND "
+ "ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id "
+ f"AND ProbeSetFreeze.Name = %s {limit_string}",
+ (dataset_name,)
+ )
+ results = cursor.fetchall()
+ trait_ids = [result[0] for result in results]
+ trait_names = [result[1] for result in results]
+ dataset_id = results[0][2]
+ return trait_ids, trait_names, data_type, dataset_id
+
+
+def get_samplelist(dataset_name):
+ group_id = get_group_id_from_dataset(dataset_name)
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT Strain.Name FROM Strain, StrainXRef "
+ "WHERE StrainXRef.StrainId = Strain.Id AND "
+ "StrainXRef.InbredSetId = %s",
+ (group_id,)
+ )
+ # sample list
+ return [result[0] for result in cursor.fetchall()]
+
+
+def get_group_id_from_dataset(dataset_name):
+ result = ()
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ if "Publish" in dataset_name:
+ cursor.execute(
+ "SELECT InbredSet.Id FROM "
+ "InbredSet, PublishFreeze "
+ "WHERE PublishFreeze.InbredSetId = InbredSet.Id "
+ "AND PublishFreeze.Name = %s",
+ (dataset_name,)
+ )
+ elif "Geno" in dataset_name:
+ cursor.execute(
+ "SELECT InbredSet.Id FROM "
+ "InbredSet, GenoFreeze WHERE "
+ "GenoFreeze.InbredSetId = InbredSet.Id "
+ "AND GenoFreeze.Name = %s",
+ (dataset_name,)
+ )
+ else:
+ cursor.execute(
+ "SELECT InbredSet.Id FROM "
+ "InbredSet, ProbeSetFreeze, "
+ "ProbeFreeze WHERE "
+ "ProbeFreeze.InbredSetId = InbredSet.Id "
+ "AND ProbeFreeze.Id = ProbeSetFreeze.ProbeFreezeId "
+ "AND ProbeSetFreeze.Name = %s",
+ (dataset_name,)
+ )
+ if result := cursor.fetchone():
+ return result[0]
+ return None
+
+
+def get_group_id(group_name):
+ with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT InbredSet.Id FROM InbredSet "
+ "WHERE InbredSet.Name = %s",
+ (group_name,)
+ )
+ if group_id := cursor.fetchone():
+ return group_id[0]
+ return None
generated by cgit v1.2.3 (git 2.44.0) at 2024-11-22 08:07:41 +0000