From e2d0dd24dd181322daf40a282370e79df23fc172 Mon Sep 17 00:00:00 2001
From: zsloan
Date: Thu, 15 Oct 2020 14:40:09 -0500
Subject: Put the correlation descriptions inside of a div so that they could
 have their width set in the same way as other sections of the
 correlation/mapping options

---
 .../show_trait_calculate_correlations.html         | 62 +++++++++++-----------
 1 file changed, 32 insertions(+), 30 deletions(-)

diff --git a/wqflask/wqflask/templates/show_trait_calculate_correlations.html b/wqflask/wqflask/templates/show_trait_calculate_correlations.html
index 00fdfc21..600664e2 100644
--- a/wqflask/wqflask/templates/show_trait_calculate_correlations.html
+++ b/wqflask/wqflask/templates/show_trait_calculate_correlations.html
@@ -114,35 +114,37 @@
       </div>
     </div>
     <div class="col-xs-4">
-      <span id="sample_r_desc" class="correlation_desc">
-          The <a href="http://genenetwork.org/correlationAnnotation.html#genetic_r">Sample Correlation</a>
-          is computed
-          between trait data and any
-          other traits in the sample database selected above. Use
-          <a href="http://www.genenetwork.org/glossary.html#Correlations">Spearman
-          Rank</a>
-          when the sample size is small (&lt;20) or when there are influential outliers.
-      </span>
-      <span id="lit_r_desc" style="display: none;" class="correlation_desc">
-          The <a href="http://genenetwork.org/correlationAnnotation.html#literatureCorr">Literature Correlation</a>
-          (Lit r) between
-          this gene and all other genes is computed<br>
-          using the <a href="https://grits.eecs.utk.edu/sgo/sgo.html">
-          Semantic Gene Organizer</a>
-          and human, rat, and mouse data from PubMed.
-          Values are ranked by Lit r, but Sample r and Tissue r are also displayed.<br>
-          <a href="http://genenetwork.org/glossary.html#Literature">More on using Lit r</a>
-      </span>
-      <span id="tissue_r_desc" style="display: none;" class="correlation_desc">
-          The <a href="http://genenetwork.org/webqtl/main.py?FormID=tissueCorrelation">Tissue Correlation</a>
-          (Tissue r)
-          estimates the similarity of expression of two genes
-          or transcripts across different cells, tissues, or organs
-          (<a href="http://genenetwork.org/correlationAnnotation.html#tissueCorr">glossary</a>).
-          Tissue correlations
-          are generated by analyzing expression in multiple samples usually taken from single cases.<br>
-          <strong>Pearson</strong> and <strong>Spearman Rank</strong> correlations have been
-          computed for all pairs of genes using data from mouse samples.<br>
-      </span>
+      <div class="section-form-div">
+        <span id="sample_r_desc" class="correlation_desc">
+            The <a href="http://genenetwork.org/correlationAnnotation.html#genetic_r">Sample Correlation</a>
+            is computed
+            between trait data and any
+            other traits in the sample database selected above. Use
+            <a href="http://www.genenetwork.org/glossary.html#Correlations">Spearman
+            Rank</a>
+            when the sample size is small (&lt;20) or when there are influential outliers.
+        </span>
+        <span id="lit_r_desc" style="display: none;" class="correlation_desc">
+            The <a href="http://genenetwork.org/correlationAnnotation.html#literatureCorr">Literature Correlation</a>
+            (Lit r) between
+            this gene and all other genes is computed<br>
+            using the <a href="https://grits.eecs.utk.edu/sgo/sgo.html">
+            Semantic Gene Organizer</a>
+            and human, rat, and mouse data from PubMed.
+            Values are ranked by Lit r, but Sample r and Tissue r are also displayed.<br>
+            <a href="http://genenetwork.org/glossary.html#Literature">More on using Lit r</a>
+        </span>
+        <span id="tissue_r_desc" style="display: none;" class="correlation_desc">
+            The <a href="http://genenetwork.org/webqtl/main.py?FormID=tissueCorrelation">Tissue Correlation</a>
+            (Tissue r)
+            estimates the similarity of expression of two genes
+            or transcripts across different cells, tissues, or organs
+            (<a href="http://genenetwork.org/correlationAnnotation.html#tissueCorr">glossary</a>).
+            Tissue correlations
+            are generated by analyzing expression in multiple samples usually taken from single cases.<br>
+            <strong>Pearson</strong> and <strong>Spearman Rank</strong> correlations have been
+            computed for all pairs of genes using data from mouse samples.<br>
+        </span>
+      </div>
     </div>
   </div>
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