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-rw-r--r--wqflask/wqflask/marker_regression/run_mapping.py26
1 files changed, 24 insertions, 2 deletions
diff --git a/wqflask/wqflask/marker_regression/run_mapping.py b/wqflask/wqflask/marker_regression/run_mapping.py
index 72844903..8f051c14 100644
--- a/wqflask/wqflask/marker_regression/run_mapping.py
+++ b/wqflask/wqflask/marker_regression/run_mapping.py
@@ -395,7 +395,7 @@ class RunMapping(object):
total_markers = len(self.qtl_results)
with Bench("Exporting Results"):
- export_mapping_results(self.dataset, self.this_trait, self.qtl_results, self.mapping_results_path, self.mapping_scale, self.score_type)
+ export_mapping_results(self.dataset, self.this_trait, self.qtl_results, self.mapping_results_path, self.mapping_scale, self.score_type, self.transform, self.covariates, self.n_samples)
with Bench("Trimming Markers for Figure"):
if len(self.qtl_results) > 30000:
@@ -504,14 +504,36 @@ class RunMapping(object):
trimmed_genotype_data.append(new_genotypes)
return trimmed_genotype_data
-def export_mapping_results(dataset, trait, markers, results_path, mapping_scale, score_type):
+def export_mapping_results(dataset, trait, markers, results_path, mapping_scale, score_type, transform, covariates, n_samples):
with open(results_path, "w+") as output_file:
output_file.write("Time/Date: " + datetime.datetime.now().strftime("%x / %X") + "\n")
output_file.write("Population: " + dataset.group.species.title() + " " + dataset.group.name + "\n")
output_file.write("Data Set: " + dataset.fullname + "\n")
+ output_file.write("N Samples: " + str(n_samples) + "\n")
+ if len(transform) > 0:
+ transform_text = "Transform - "
+ if transform == "qnorm":
+ transform_text += "Quantile Normalized"
+ elif transform == "log2" or transform == "log10":
+ transform_text += transform.capitalize()
+ elif transform == "sqrt":
+ transform_text += "Square Root"
+ elif transform == "zscore":
+ transform_text += "Z-Score"
+ elif transform == "invert":
+ transform_text += "Invert +/-"
+ else:
+ transform_text = ""
+ output_file.write(transform_text + "\n")
if dataset.type == "ProbeSet":
output_file.write("Gene Symbol: " + trait.symbol + "\n")
output_file.write("Location: " + str(trait.chr) + " @ " + str(trait.mb) + " Mb\n")
+ if len(covariates) > 0:
+ output_file.write("Cofactors (dataset - trait):\n")
+ for covariate in covariates.split(","):
+ trait_name = covariate.split(":")[0]
+ dataset_name = covariate.split(":")[1]
+ output_file.write(dataset_name + " - " + trait_name + "\n")
output_file.write("\n")
output_file.write("Name,Chr,")
if score_type.lower() == "-logP":