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| author | zsloan | 2020-11-02 13:16:59 -0600 |
|---|---|---|
| committer | zsloan | 2020-11-02 13:16:59 -0600 |
| commit | 2864bf07f919dacc72b5df590b140881bbe8dc0c (patch) | |
| tree | f05f57a030fdfcca6a209f721af5e55d7b73628d | |
| parent | ad716823091959a5332173a0fd2a040c969d2712 (diff) | |
| download | genenetwork2-2864bf07f919dacc72b5df590b140881bbe8dc0c.tar.gz | |
Changed correlation page logic to skip over traits that share fewer than 6 samples + traits that user doesn't have permission to access
* wqflask/wqflask/correlation/show_corr_results.py - Moved the num_overlap check so that it never attempts to calculate the correlation if it's too low + checked if trait_object is None in the main loop (since it would be returned as None if the user doesn't have permissions
| -rw-r--r-- | wqflask/wqflask/correlation/show_corr_results.py | 19 |
1 files changed, 11 insertions, 8 deletions
diff --git a/wqflask/wqflask/correlation/show_corr_results.py b/wqflask/wqflask/correlation/show_corr_results.py index e710bacd..4c2b64ba 100644 --- a/wqflask/wqflask/correlation/show_corr_results.py +++ b/wqflask/wqflask/correlation/show_corr_results.py @@ -184,6 +184,8 @@ class CorrelationResults(object): for _trait_counter, trait in enumerate(list(self.correlation_data.keys())[:self.return_number]): trait_object = create_trait(dataset=self.target_dataset, name=trait, get_qtl_info=True, get_sample_info=False) + if not trait_object: + continue if self.target_dataset.type == "ProbeSet" or self.target_dataset.type == "Geno": #ZS: Convert trait chromosome to an int for the location range option @@ -434,15 +436,15 @@ class CorrelationResults(object): self.this_trait_vals, target_vals, num_overlap = corr_result_helpers.normalize_values(self.this_trait_vals, target_vals) - #ZS: 2015 could add biweight correlation, see http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465711/ - if self.corr_method == 'bicor': - sample_r, sample_p = do_bicor(self.this_trait_vals, target_vals) - elif self.corr_method == 'pearson': - sample_r, sample_p = scipy.stats.pearsonr(self.this_trait_vals, target_vals) - else: - sample_r, sample_p = scipy.stats.spearmanr(self.this_trait_vals, target_vals) - if num_overlap > 5: + #ZS: 2015 could add biweight correlation, see http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465711/ + if self.corr_method == 'bicor': + sample_r, sample_p = do_bicor(self.this_trait_vals, target_vals) + elif self.corr_method == 'pearson': + sample_r, sample_p = scipy.stats.pearsonr(self.this_trait_vals, target_vals) + else: + sample_r, sample_p = scipy.stats.spearmanr(self.this_trait_vals, target_vals) + if numpy.isnan(sample_r): pass else: @@ -635,3 +637,4 @@ def get_header_fields(data_type, corr_method): 'Sample p(r)'] return header_fields + |