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authorAlexander Kabui2021-05-13 08:25:42 +0300
committerBonfaceKilz2021-05-13 12:03:46 +0300
commit75b4e74dede48c59e07d8f15d2db4b5d6289c064 (patch)
treee1c1229ebdfc849d9c12b162c1949149b529a67e
parent413425b8ed3c69947b49ca366b210d69d2173805 (diff)
downloadgenenetwork2-75b4e74dede48c59e07d8f15d2db4b5d6289c064.tar.gz
integrate comute corr for top results in ui
-rw-r--r--wqflask/wqflask/correlation/correlation_gn3_api.py68
-rw-r--r--wqflask/wqflask/templates/test_correlation_page.html5
2 files changed, 54 insertions, 19 deletions
diff --git a/wqflask/wqflask/correlation/correlation_gn3_api.py b/wqflask/wqflask/correlation/correlation_gn3_api.py
index e5638b5a..dec84728 100644
--- a/wqflask/wqflask/correlation/correlation_gn3_api.py
+++ b/wqflask/wqflask/correlation/correlation_gn3_api.py
@@ -137,16 +137,19 @@ def compute_correlation(start_vars, method="pearson"):
(this_dataset, this_trait, target_dataset,
sample_data) = create_target_this_trait(start_vars)
+ target_dataset_type = target_dataset.type
+ this_dataset_type = this_dataset.type
+
method = start_vars['corr_sample_method']
corr_return_results = int(start_vars.get("corr_return_results", 100))
corr_input_data = {}
if corr_type == "sample":
- (this_trait_data, target_dataset) = fetch_sample_data(
+ (this_trait_data, target_dataset_data) = fetch_sample_data(
start_vars, this_trait, this_dataset, target_dataset)
correlation_results = compute_all_sample_correlation(corr_method=method,
this_trait=this_trait_data,
- target_dataset=target_dataset)
+ target_dataset=target_dataset_data)
elif corr_type == "tissue":
trait_symbol_dict = this_dataset.retrieve_genes("Symbol")
@@ -175,31 +178,62 @@ def compute_correlation(start_vars, method="pearson"):
conn=conn, trait_lists=list(geneid_dict.items()),
species=species, gene_id=this_trait_geneid)
- # correlation_results = correlation_results[0:corr_return_results]
- # if corr_type != "tissue" and this_dataset.type == "ProbeSet" and target_dataset.type == "ProbeSet":
- # pass
- # # tissue_result = tissue_for_trait_lists(
- # # correlation_results, this_dataset, this_trait)
+ correlation_results = correlation_results[0:corr_return_results]
- # # correlation_results = merge_correlation_results(
- # # correlation_results, tissue_result)
+ compute_all = True
+
+ correlation_results = compute_corr_for_top_results(correlation_results,
+ this_trait,
+ this_dataset,
+ target_dataset,
+ corr_type)
+
+ # if corr_type != "tissue" and this_dataset_type == "ProbeSet" and target_dataset_type == "ProbeSet":
+
+ # tissue_result = tissue_for_trait_lists(
+ # correlation_results, this_dataset, this_trait)
+
+ # if corr_type != "lit" and this_dataset_type == "ProbeSet" and target_dataset_type == "ProbeSet":
+ # lit_result = lit_for_trait_list(
+ # correlation_results, this_dataset, this_trait)
- # if corr_type != "lit" and this_dataset.type == "ProbeSet" and target_dataset.type == "ProbeSet":
- # pass
- # # lit is very slow
- # # lit_result = lit_for_trait_list(correlation_results, this_dataset, this_trait)
- # # correlation_results = merge_correlation_results(correlation_results,lit_result)
# if corr_type != "sample":
- # # do sample correlation
# pass
- correlation_results = correlation_results[0:corr_return_results]
+
correlation_data = {"correlation_results": correlation_results,
"this_trait": this_trait.name,
- "target_dataset": start_vars['corr_dataset']}
+ "target_dataset": start_vars['corr_dataset'],
+ "return_results": corr_return_results}
return correlation_data
+def compute_corr_for_top_results(correlation_results,
+ this_trait,
+ this_dataset,
+ target_dataset,
+ corr_type):
+ if corr_type != "tissue" and this_dataset.type == "ProbeSet" and target_dataset.type == "ProbeSet":
+
+ tissue_result = tissue_for_trait_lists(
+ correlation_results, this_dataset, this_trait)
+
+ correlation_results = merge_correlation_results(
+ correlation_results, tissue_result)
+
+ if corr_type != "lit" and this_dataset.type == "ProbeSet" and target_dataset.type == "ProbeSet":
+ lit_result = lit_for_trait_list(
+ correlation_results, this_dataset, this_trait)
+
+ correlation_results = merge_correlation_results(
+ correlation_results, lit_result)
+
+ if corr_type != "sample":
+ pass
+
+ return correlation_results
+
+
def do_lit_correlation(this_trait, this_dataset):
"""function for fetching lit inputs"""
geneid_dict = this_dataset.retrieve_genes("GeneId")
diff --git a/wqflask/wqflask/templates/test_correlation_page.html b/wqflask/wqflask/templates/test_correlation_page.html
index 186de4b7..0809b65e 100644
--- a/wqflask/wqflask/templates/test_correlation_page.html
+++ b/wqflask/wqflask/templates/test_correlation_page.html
@@ -42,7 +42,7 @@
{% block content %}
<div class="correlation-title">
- <h3>Correlation Results for <span>{{target_dataset}}</span> against <span><a href="">{{this_trait}}</a></span> for the top <span>all</span> Results</h3>
+ <h3>Correlation Results for <span>{{target_dataset}}</span> against <span><a href="">{{this_trait}}</a></span> for the top <span>{{return_results}}</span> Results</h3>
</div>
<div class="header-toggle-vis">
<h4 style="font-weight: bolder;padding: 5px 3px;">Toggle Columns</h4>
@@ -137,7 +137,8 @@ console.log(correlationResults)
{
"targets":2,
"render":(data,type,row)=>{
- let urlLink = "/show_trait?trait_id=1453207_at&dataset=HC_M2_0606_P"
+ // should use a dynamic dataset name
+ let urlLink = `/show_trait?trait_id=${data}&dataset=HC_M2_0606_P`
let traitLink = `<a href=${urlLink}>${data}</a>`
return traitLink
},