-<p><strong>Calculation of trees from alignments</strong></p>
-<p>Trees are calculated on either the complete alignment, or just the
-currently selected group of sequences, using the functions in the
-<strong>Calculate→Calculate tree</strong> submenu.
-Once calculated, trees are displayed in a new <a
-href="../calculations/treeviewer.html">tree viewing window</a>. There are
-four different calculations, using one of two distance measures and
-constructing the tree from one of two algorithms :
-</p>
-<p><strong>Distance Measures</strong></p>
-<p>Trees are calculated on the basis of a measure of similarity
-between each pair of sequences in the alignment :
-<ul>
-<li><strong>PID</strong><br>The percentage identity between the two
-sequences at each aligned position.<ul><li>PID = Number of equivalent
-aligned non-gap symbols * 100 / Smallest number of non-gap positions
-in either of both sequences<br><em>This is essentially the 'number of
-identical bases (or residues) per 100 base pairs (or residues)'.</em></li></ul>
-<li><strong>BLOSUM62</strong><br>The sum of BLOSUM62 scores for the
-residue pair at each aligned position.
-</ul>
-</p>
-<p><strong>Tree Construction Methods</strong></p>
-<p>Jalview currently supports two kinds of agglomerative clustering
-methods. These are not intended to substitute for rigorous
-phylogenetic tree construction, and may fail on very large alignments.
-<ul>
-<li><strong>UPGMA tree</strong><br>
- UPGMA stands for Unweighted Pair-Group Method using Arithmetic
- averages. Clusters are iteratively formed and extended by finding a
- non-member sequence with the lowest average dissimilarity over the
- cluster members.
-<p></p>
-</li>
-<li><strong>Neighbour Joining tree</strong><br>
- First described in 1987 by Saitou and Nei, this method applies a
- greedy algorithm to find the tree with the shortest branch
- lengths.<br>
- This method, as implemented in Jalview, is considerably more
- expensive than UPGMA.
-</li>
-</ul>
-</p>
-<p>A newly calculated tree will be displayed in a new <a
-href="../calculations/treeviewer.html">tree viewing window</a>. In
-addition, a new entry with the same tree viewer window name will be added in the Sort
-menu so that the alignment can be reordered to reflect the ordering of
-the leafs of the tree. If the tree was calculated on a selected region
-of the alignment, then the title of the tree view will reflect this.</p>
+ <p>
+ <strong>Calculation of trees from alignments</strong>
+ </p>
+ <p>
+ Trees are calculated on either the complete alignment, or just the
+ currently selected group of sequences, via the <a href="calculations.html">calculations dialog</a> opened from the <strong>Calculate→Calculate
+ Tree or PCA...</strong> menu entry. Once calculated, trees are displayed in a new <a
+ href="../calculations/treeviewer.html">tree viewing
+ window</a>. There are four different calculations, using one of two
+ distance measures and constructing the tree from one of two
+ algorithms :
+ </p>
+ <p>
+ <strong>Distance Measures</strong>
+ </p>
+ <p>Trees are calculated on the basis of a measure of similarity
+ between each pair of sequences in the alignment :
+ <ul>
+ <li><strong>PID</strong><br>The percentage identity
+ between the two sequences at each aligned position.
+ <ul>
+ <li>PID = Number of equivalent aligned non-gap symbols *
+ 100 / Smallest number of non-gap positions in either of both
+ sequences<br> <em>This is essentially the 'number of
+ identical bases (or residues) per 100 base pairs (or
+ residues)'.</em>
+ </li>
+ </ul>
+ <li><strong>BLOSUM62, PAM250, DNA</strong><br />These options
+ use one of the available substitution matrices to compute a sum of
+ scores for the residue pairs at each aligned position.
+ <ul>
+ <li>For details about each model, see the <a
+ href="scorematrices.html">list of built-in score
+ matrices</a>.
+ </li>
+ </ul></li>
+ <li><strong>Sequence Feature Similarity</strong><br>Trees
+ are constructed from a distance matrix formed from Jaccard
+ distances between sequence features observed at each column of the
+ alignment.
+ <ul>
+ <li>Similarity at column <em>i</em> = (Total number of
+ features displayed - Sum of number of features in common at <em>i</em>)
+ <br />Similarities are summed over all columns and divided by
+ the number of columns. <br />Since the total number of
+ feature types is constant over all columns of the alignment,
+ we do not scale the matrix, so tree distances can be
+ interpreted as the average number of features that differ over
+ all sites in the aligned region.
+ </li>