diff options
Diffstat (limited to 'wqflask/wqflask/api/mapping.py')
| -rw-r--r-- | wqflask/wqflask/api/mapping.py | 42 |
1 files changed, 22 insertions, 20 deletions
diff --git a/wqflask/wqflask/api/mapping.py b/wqflask/wqflask/api/mapping.py index d830cefc..f8b0d8bd 100644 --- a/wqflask/wqflask/api/mapping.py +++ b/wqflask/wqflask/api/mapping.py @@ -1,24 +1,23 @@ -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 base.trait import create_trait, 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__ ) +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 = 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 = create_trait(dataset=dataset, name=start_vars['trait_id']) this_trait = retrieve_sample_data(this_trait, dataset) samples = [] @@ -38,26 +37,32 @@ def do_mapping_for_api(start_vars): 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. + # ZS: It seems to take an empty string as default. This should probably be changed. + covariates = "" 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] + # ZS: gemma_mapping returns both results and the filename for LOCO, so need to only grab the former for api + if mapping_params['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']) + 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']) + 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']) + 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']] @@ -76,7 +81,6 @@ def do_mapping_for_api(start_vars): return result_markers, None - def initialize_parameters(start_vars, dataset, this_trait): mapping_params = {} @@ -120,7 +124,7 @@ def initialize_parameters(start_vars, dataset, this_trait): mapping_params['maf'] = 0.01 if 'maf' in start_vars: - mapping_params['maf'] = start_vars['maf'] # Minor allele frequency + mapping_params['maf'] = start_vars['maf'] # Minor allele frequency mapping_params['use_loco'] = True if 'use_loco' in start_vars: @@ -137,5 +141,3 @@ def initialize_parameters(start_vars, dataset, this_trait): mapping_params['perm_check'] = False return mapping_params - - |