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-rw-r--r--wqflask/wqflask/api/mapping.py263
-rw-r--r--wqflask/wqflask/api/router.py63
2 files changed, 188 insertions, 138 deletions
diff --git a/wqflask/wqflask/api/mapping.py b/wqflask/wqflask/api/mapping.py
index 83c61796..d830cefc 100644
--- a/wqflask/wqflask/api/mapping.py
+++ b/wqflask/wqflask/api/mapping.py
@@ -1,122 +1,141 @@
-from __future__ import absolute_import, division, print_function
-
-import string
-
-from base import data_set
-from base import webqtlConfig
-from base.trait import GeneralTrait, retrieve_sample_data
-
-from utility import helper_functions
-from wqflask.marker_regression import gemma_mapping, rqtl_mapping, qtlreaper_mapping, plink_mapping
-
-import utility.logger
-logger = utility.logger.getLogger(__name__ )
-
-def do_mapping_for_api(start_vars):
- assert('db' in start_vars)
- assert('trait_id' in start_vars)
-
- dataset = data_set.create_dataset(dataset_name = start_vars['db'])
- dataset.group.get_markers()
- this_trait = GeneralTrait(dataset = dataset, name = start_vars['trait_id'])
- this_trait = retrieve_sample_data(this_trait, dataset)
-
- samples = []
- vals = []
-
- for sample in dataset.group.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")
-
- mapping_params = initialize_parameters(start_vars, dataset, this_trait)
-
- covariates = "" #ZS: It seems to take an empty string as default. This should probably be changed.
-
- if mapping_params['mapping_method'] == "gemma":
- header_row = ["name", "chr", "Mb", "lod_score", "p_value"]
- if mapping_params['use_loco'] == "True": #ZS: gemma_mapping returns both results and the filename for LOCO, so need to only grab the former for api
- 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['mapping_method'] == "rqtl":
- header_row = ["name", "chr", "Mb", "lod_score"]
- if mapping_params['num_perm'] > 0:
- _sperm_output, _suggestive, _significant, result_markers = rqtl_mapping.run_rqtl_geno(vals, dataset, mapping_params['rqtl_method'], mapping_params['rqtl_model'],
- mapping_params['perm_check'], mapping_params['num_perm'],
- mapping_params['do_control'], mapping_params['control_marker'],
- mapping_params['manhattan_plot'], mapping_params['pair_scan'])
- else:
- result_markers = rqtl_mapping.run_rqtl_geno(vals, dataset, mapping_params['rqtl_method'], mapping_params['rqtl_model'],
- mapping_params['perm_check'], mapping_params['num_perm'],
- mapping_params['do_control'], mapping_params['control_marker'],
- mapping_params['manhattan_plot'], mapping_params['pair_scan'])
-
- 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
-
-
-def initialize_parameters(start_vars, dataset, this_trait):
- mapping_params = {}
- 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'] = False
- if 'use_loco' in start_vars:
- if start_vars['use_loco'].lower() != "false":
- mapping_params['use_loco'] = start_vars['use_loco']
-
- 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
-
- return mapping_params
-
-
+from __future__ import absolute_import, division, print_function
+
+import string
+
+from base import data_set
+from base import webqtlConfig
+from base.trait import GeneralTrait, retrieve_sample_data
+
+from utility import helper_functions
+from wqflask.marker_regression import gemma_mapping, rqtl_mapping, qtlreaper_mapping, plink_mapping
+
+import utility.logger
+logger = utility.logger.getLogger(__name__ )
+
+def do_mapping_for_api(start_vars):
+ assert('db' in start_vars)
+ assert('trait_id' in start_vars)
+
+ dataset = data_set.create_dataset(dataset_name = start_vars['db'])
+ dataset.group.get_markers()
+ this_trait = GeneralTrait(dataset = dataset, name = start_vars['trait_id'])
+ this_trait = retrieve_sample_data(this_trait, dataset)
+
+ samples = []
+ vals = []
+
+ for sample in dataset.group.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")
+
+ mapping_params = initialize_parameters(start_vars, dataset, this_trait)
+
+ covariates = "" #ZS: It seems to take an empty string as default. This should probably be changed.
+
+ if mapping_params['mapping_method'] == "gemma":
+ header_row = ["name", "chr", "Mb", "lod_score", "p_value"]
+ if mapping_params['use_loco'] == "True": #ZS: gemma_mapping returns both results and the filename for LOCO, so need to only grab the former for api
+ 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['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_geno(vals, dataset, mapping_params['rqtl_method'], mapping_params['rqtl_model'],
+ mapping_params['perm_check'], mapping_params['num_perm'],
+ mapping_params['do_control'], mapping_params['control_marker'],
+ mapping_params['manhattan_plot'], mapping_params['pair_scan'])
+ else:
+ result_markers = rqtl_mapping.run_rqtl_geno(vals, dataset, mapping_params['rqtl_method'], mapping_params['rqtl_model'],
+ mapping_params['perm_check'], mapping_params['num_perm'],
+ mapping_params['do_control'], mapping_params['control_marker'],
+ mapping_params['manhattan_plot'], mapping_params['pair_scan'])
+
+ if mapping_params['limit_to']:
+ result_markers = result_markers[:mapping_params['limit_to']]
+
+ if mapping_params['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
+
+ return mapping_params
+
+
diff --git a/wqflask/wqflask/api/router.py b/wqflask/wqflask/api/router.py
index 8e2cbbdc..cbff6e83 100644
--- a/wqflask/wqflask/api/router.py
+++ b/wqflask/wqflask/api/router.py
@@ -293,7 +293,7 @@ def get_dataset_info(dataset_name, group_name = None, file_format="json"):
@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)
+ 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"
@@ -367,6 +367,10 @@ def fetch_traits(dataset_name, file_format = "json"):
field_list = ["Id", "PhenotypeId", "PublicationId", "Locus", "LRS", "Additive", "Sequence"]
+ if 'limit_to' in request.args:
+ limit_number = request.args['limit_to']
+ query += "LIMIT " + str(limit_number)
+
if file_format == "json":
filename = dataset_name + "_traits.json"
@@ -408,7 +412,7 @@ def fetch_traits(dataset_name, file_format = "json"):
@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)
+ 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)
@@ -496,7 +500,7 @@ def all_sample_data(dataset_name, file_format = "csv"):
output.headers["Content-type"] = "text/csv"
return output
else:
- return return_error(code=204, source=request.url_rule.rule, title="No Results", details="")
+ 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="")
@@ -669,25 +673,35 @@ def get_corr_results():
@app.route("/api/v_{}/mapping".format(version), methods=("GET",))
def get_mapping_results():
- results = mapping.do_mapping_for_api(request.args)
+ results, format = mapping.do_mapping_for_api(request.args)
if len(results) > 0:
- filename = "mapping_" + datetime.datetime.utcnow().strftime("%b_%d_%Y_%I:%M%p") + ".csv"
+ if format == "csv":
+ filename = "mapping_" + datetime.datetime.utcnow().strftime("%b_%d_%Y_%I:%M%p") + ".csv"
- si = StringIO.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"
+ si = StringIO.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
+ 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/<path:group_name>".format(version))
@app.route("/api/v_{}/genotypes/<path:group_name>.<path:file_format>".format(version))
def get_genotypes(group_name, file_format="csv"):
+ limit_num = None
+ if 'limit_to' in request.args:
+ if request.args['limit_to'].isdigit():
+ limit_num = int(request.args['limit_to'])
+
si = StringIO.StringIO()
if file_format == "csv" or file_format == "geno":
filename = group_name + ".geno"
@@ -695,11 +709,15 @@ def get_genotypes(group_name, file_format="csv"):
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 i >= limit_num:
+ break
output_lines.append(line.split())
+ i += 1
csv_writer = csv.writer(si, delimiter = "\t", escapechar = "\\", quoting = csv.QUOTE_NONE)
else:
@@ -710,8 +728,12 @@ def get_genotypes(group_name, file_format="csv"):
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 i >= limit_num:
+ break
output_lines.append([line.strip() for line in line.split(",")])
+ i += 1
csv_writer = csv.writer(si, delimiter = ",")
else:
@@ -736,7 +758,13 @@ def return_error(code, source, title, details):
return flask.jsonify(json_ob)
-def get_dataset_trait_ids(dataset_name):
+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 = ""
+
if "Geno" in dataset_name:
data_type = "Geno" #ZS: Need to pass back the dataset type
query = """
@@ -748,7 +776,8 @@ def get_dataset_trait_ids(dataset_name):
Geno.Id = GenoXRef.GenoId AND
GenoXRef.GenoFreezeId = GenoFreeze.Id AND
GenoFreeze.Name = "{0}"
- """.format(dataset_name)
+ {1}
+ """.format(dataset_name, limit_string)
results = g.db.execute(query).fetchall()
@@ -769,7 +798,8 @@ def get_dataset_trait_ids(dataset_name):
PublishXRef
WHERE
PublishXRef.InbredSetId = "{0}"
- """.format(dataset_id)
+ {1}
+ """.format(dataset_id, limit_string)
results = g.db.execute(query).fetchall()
@@ -788,7 +818,8 @@ def get_dataset_trait_ids(dataset_name):
ProbeSet.Id = ProbeSetXRef.ProbeSetId AND
ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND
ProbeSetFreeze.Name = "{0}"
- """.format(dataset_name)
+ {1}
+ """.format(dataset_name, limit_string)
results = g.db.execute(query).fetchall()
generated by cgit v1.2.3 (git 2.44.0) at 2024-11-22 21:56:12 +0000