diff options
| -rw-r--r-- | wqflask/wqflask/correlation/show_corr_results.py | 81 | ||||
| -rw-r--r-- | wqflask/wqflask/marker_regression/display_mapping_results.py | 17 |
2 files changed, 54 insertions, 44 deletions
diff --git a/wqflask/wqflask/correlation/show_corr_results.py b/wqflask/wqflask/correlation/show_corr_results.py index 0c6b8a2b..031c7a16 100644 --- a/wqflask/wqflask/correlation/show_corr_results.py +++ b/wqflask/wqflask/correlation/show_corr_results.py @@ -207,35 +207,20 @@ class CorrelationResults(object): elif (self.max_location_mb != None) and (float(trait_object.mb) > float(self.max_location_mb)): continue - (trait_object.sample_r, - trait_object.sample_p, - trait_object.num_overlap) = self.correlation_data[trait] - - # Set some sane defaults - trait_object.tissue_corr = 0 - trait_object.tissue_pvalue = 0 - trait_object.lit_corr = 0 - if self.corr_type == "tissue" and tissue_corr_data != None: - trait_object.tissue_corr = tissue_corr_data[trait][1] - trait_object.tissue_pvalue = tissue_corr_data[trait][2] - elif self.corr_type == "lit": - trait_object.lit_corr = lit_corr_data[trait][1] - self.correlation_results.append(trait_object) - else: - (trait_object.sample_r, - trait_object.sample_p, - trait_object.num_overlap) = self.correlation_data[trait] - - # Set some sane defaults - trait_object.tissue_corr = 0 - trait_object.tissue_pvalue = 0 - trait_object.lit_corr = 0 - if self.corr_type == "tissue": - trait_object.tissue_corr = tissue_corr_data[trait][1] - trait_object.tissue_pvalue = tissue_corr_data[trait][2] - elif self.corr_type == "lit": - trait_object.lit_corr = lit_corr_data[trait][1] - self.correlation_results.append(trait_object) + (trait_object.sample_r, + trait_object.sample_p, + trait_object.num_overlap) = self.correlation_data[trait] + + # Set some sane defaults + trait_object.tissue_corr = 0 + trait_object.tissue_pvalue = 0 + trait_object.lit_corr = 0 + if self.corr_type == "tissue" and tissue_corr_data != None: + trait_object.tissue_corr = tissue_corr_data[trait][1] + trait_object.tissue_pvalue = tissue_corr_data[trait][2] + elif self.corr_type == "lit": + trait_object.lit_corr = lit_corr_data[trait][1] + self.correlation_results.append(trait_object) self.target_dataset.get_trait_info(self.correlation_results, self.target_dataset.group.species) @@ -473,13 +458,16 @@ class CorrelationResults(object): if not value.strip().lower() == 'x': self.sample_data[str(sample)] = float(value) -def generate_corr_json(corr_results, this_trait, dataset, target_dataset): +def generate_corr_json(corr_results, this_trait, dataset, target_dataset, for_api = False): results_list = [] for i, trait in enumerate(corr_results): results_dict = {} - results_dict['checkbox'] = "<INPUT TYPE='checkbox' NAME='searchResult' class='checkbox trait_checkbox' style='padding-right: 0px;' VALUE='" + user_manager.data_hmac('{}:{}'.format(trait.name, trait.dataset.name)) + "'>" - results_dict['index'] = i + 1 - results_dict['trait_id'] = "<a href='/show_trait?trait_id="+str(trait.name)+"&dataset="+str(dataset.name)+"'>"+str(trait.name)+"</a>" + if not for_api: + results_dict['checkbox'] = "<INPUT TYPE='checkbox' NAME='searchResult' class='checkbox trait_checkbox' style='padding-right: 0px;' VALUE='" + user_manager.data_hmac('{}:{}'.format(trait.name, trait.dataset.name)) + "'>" + results_dict['index'] = i + 1 + results_dict['trait_id'] = "<a href='/show_trait?trait_id="+str(trait.name)+"&dataset="+str(dataset.name)+"'>"+str(trait.name)+"</a>" + else: + results_dict['trait_id'] = trait.name if target_dataset.type == "ProbeSet": results_dict['symbol'] = trait.symbol results_dict['description'] = trait.description_display @@ -494,7 +482,10 @@ def generate_corr_json(corr_results, this_trait, dataset, target_dataset): results_dict['additive'] = "%0.3f" % float(trait.additive) else: results_dict['additive'] = "N/A" - results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % float(trait.sample_r) + "</a>" + if for_api: + results_dict['sample_r'] = "%0.3f" % float(trait.sample_r) + else: + results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % float(trait.sample_r) + "</a>" results_dict['num_overlap'] = trait.num_overlap results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) if trait.lit_corr == "" or trait.lit_corr == 0: @@ -509,21 +500,35 @@ def generate_corr_json(corr_results, this_trait, dataset, target_dataset): results_dict['description'] = trait.description_display results_dict['authors'] = trait.authors if trait.pubmed_id: - results_dict['pubmed'] = "<a href='" + trait.pubmed_link + "'> " + trait.pubmed_text + "</a>" + if for_api: + results_dict['pubmed_id'] = trait.pubmed_id + results_dict['year'] = trait.pubmed_text + else: + results_dict['pubmed'] = "<a href='" + trait.pubmed_link + "'> " + trait.pubmed_text + "</a>" else: - results_dict['pubmed'] = "N/A" + if for_api: + results_dict['pubmed_id'] = "N/A" + results_dict['year'] = "N/A" + else: + results_dict['pubmed'] = "N/A" results_dict['lrs_score'] = trait.LRS_score_repr results_dict['lrs_location'] = trait.LRS_location_repr if trait.additive != "": results_dict['additive'] = "%0.3f" % float(trait.additive) else: results_dict['additive'] = "N/A" - results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % trait.sample_r + "</a>" + if for_api: + results_dict['sample_r'] = "%0.3f" % trait.sample_r + else: + results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % trait.sample_r + "</a>" results_dict['num_overlap'] = trait.num_overlap results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) else: results_dict['lrs_location'] = trait.LRS_location_repr - results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % float(trait.sample_r) + "</a>" + if for_api: + results_dict['sample_r'] = "%0.3f" % trait.sample_r + else: + results_dict['sample_r'] = "<a target='_blank' href='corr_scatter_plot?dataset_1=" + str(dataset.name) + "&dataset_2=" + str(trait.dataset.name) + "&trait_1=" + str(this_trait.name) + "&trait_2=" + str(trait.name) + "'>" + "%0.3f" % float(trait.sample_r) + "</a>" results_dict['num_overlap'] = trait.num_overlap results_dict['sample_p'] = "%0.3e" % float(trait.sample_p) diff --git a/wqflask/wqflask/marker_regression/display_mapping_results.py b/wqflask/wqflask/marker_regression/display_mapping_results.py index f4d5ca66..67cefaa6 100644 --- a/wqflask/wqflask/marker_regression/display_mapping_results.py +++ b/wqflask/wqflask/marker_regression/display_mapping_results.py @@ -346,9 +346,12 @@ class DisplayMappingResults(object): thisTrait = self.this_trait _strains, _vals, _vars, _aliases = thisTrait.export_informative() smd=[] - for ii, _val in enumerate(_vals): - temp = GeneralObject(name=_strains[ii], value=_val) - smd.append(temp) + for ii, _val in enumerate(self.vals): + if _val != "x": + temp = GeneralObject(name=self.samples[ii], value=float(_val)) + smd.append(temp) + else: + continue samplelist = list(self.genotype.prgy) for j,_geno in enumerate (self.genotype[0][1].genotype): for item in smd: @@ -1167,10 +1170,12 @@ class DisplayMappingResults(object): _strains, _vals, _vars, _aliases = thisTrait.export_informative() smd=[] - for ii, _val in enumerate(_vals): - if _strains[ii] in self.samples: - temp = GeneralObject(name=_strains[ii], value=_val) + for ii, _val in enumerate(self.vals): + if _val != "x": + temp = GeneralObject(name=self.samples[ii], value=float(_val)) smd.append(temp) + else: + continue smd.sort(lambda A, B: cmp(A.value, B.value)) smd.reverse() |