types. Sequences with similar distributions of features of the
same type will be grouped together in trees computed with this
metric. <em>This measure was introduced in Jalview 2.9</em></li>
+
+ <li><strong>Secondary Structure Similarity</strong><br>Trees are
+ generated using a distance matrix, which is constructed from Jaccard
+ distances that specifically consider the secondary structure features
+ observed at each column of the alignment.
+ <ul>
+ <li>For secondary structure similarity analysis, at any given column
+ <em>i</em>, the range of unique secondary structures is between 0 and 2,
+ reflecting the presence of helices, sheets, coils and gaps.
+ <br>The similarity at column <em>i</em> = Total
+ number of unique secondary structures (which can range from 0 to 2)
+ - Sum of the number of secondary structures in common at column
+ <em>i</em> (which can be either 0 or 1)<br>The similarity scores are
+ summed across all columns and then divided by the total number of
+ columns to calculate an average similarity score.
+ </li>
+ </ul>
+ Distance calculations are based on the secondary structures
+ currently displayed. Sequences with similar distributions of secondary
+ structures will be grouped together in trees.<br>
+ <em>The distance between two sequences is maximum when one
+ sequence has a defined secondary structure annotation track and the
+ other does not, indicating complete dissimilarity between them.
+ Whereas, the distance between two sequences is minimum when both of
+ the sequences within the comparison do not have a defined secondary
+ structure annotation track.</em>
+ </li>
</ul>
<p>
<strong>Tree Construction Methods</strong>
git://source.jalview.org / jalview.git / blobdiff