X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=help%2Fhtml%2Fcalculations%2Fpca.html;h=3529cae8f9159e0691061cdbfeddbef0b2eee416;hb=6f9d7b98943ecba292a9c0dd65b30c4d8150c98f;hp=08bc726bd1fcb43b6482a22cfbe1dd868dd3a01a;hpb=db93a1adcbe0a4eaaf06e0a70ade0d6c5c1961c3;p=jalview.git

diff --git a/help/html/calculations/pca.html b/help/html/calculations/pca.html
index 08bc726..3529cae 100755
--- a/help/html/calculations/pca.html
+++ b/help/html/calculations/pca.html
@@ -1,7 +1,7 @@
 <html>
 <!--
- * Jalview - A Sequence Alignment Editor and Viewer (Version 2.9.0b2)
- * Copyright (C) 2015 The Jalview Authors
+ * Jalview - A Sequence Alignment Editor and Viewer ($$Version-Rel$$)
+ * Copyright (C) $$Year-Rel$$ The Jalview Authors
  * 
  * This file is part of Jalview.
  * 
@@ -26,16 +26,23 @@
   <p>
     <strong>Principal Component Analysis</strong>
   </p>
+  <p>
+    A principal component analysis can be performed via the <a
+      href="calculations.html">calculations dialog</a> which is accessed
+    by selecting <strong>Calculate&#8594;Calculate Tree or
+      PCA...</strong>.
+  </p>
   <p>This calculation creates a spatial representation of the
     similarities within a selected group, or all of the sequences in an
     alignment. After the calculation finishes, a 3D viewer displays the
     set of sequences as points in 'similarity space', and similar
     sequences tend to lie near each other in the space.</p>
   <p>
-    <em>Caveats</em><br />The calculation is computationally expensive,
-    and may fail for very large sets of sequences - usually because the
-    JVM has run out of memory. A future release of Jalview will be able
-    to avoid this by executing the calculation via a web service.
+    <em>Caveats</em><br />The calculation can be computationally
+    expensive, and may fail for very large sets of sequences - usually
+    because the JVM has run out of memory. However, the PCA
+    implementation in Jalview 2.10.2 employs more memory efficient
+    matrix storage structures, allowing larger PCAs to be performed.
   </p>
 
   <p>
@@ -53,33 +60,15 @@
     <em>Calculating PCAs for aligned sequences</em><br />Jalview can
     perform PCA analysis on both proteins and nucleotide sequence
     alignments. In both cases, components are generated by an
-    eigenvector decomposition of the matrix formed from the sum of
-    substitution matrix scores at each aligned position between each
-    pair of sequences - computed with one of the available score
-    matrices, such as <a href="scorematrices.html#blosum62">BLOSUM62</a>,
+    eigenvector decomposition of the matrix formed from pairwise similarity
+    scores between each pair of sequences. The similarity score model is 
+    selected on the <a href="calculations.html">calculations dialog</a>, and
+    may use one of the available score matrices, such as 
+    <a href="scorematrices.html#blosum62">BLOSUM62</a>,
     <a href="scorematrices.html#pam250">PAM250</a>, or the <a
       href="scorematrices.html#simplenucleotide">simple single
-      nucleotide substitution matrix</a>. The options available for
-    calculation are given in the <strong><em>Change
-        Parameters</em></strong> menu.
-  </p>
-  <p>
-    <em>PCA Calculation modes</em><br /> The default Jalview
-    calculation mode (indicated when <em><strong>Jalview
-        PCA Calculation</strong></em> is ticked in the <strong><em>Change
-        Parameters</em></strong> menu) is to perform a PCA on a matrix where elements
-    in the upper diagonal give the sum of scores for mutating in one
-    direction, and the lower diagonal is the sum of scores for mutating
-    in the other. For protein substitution models like BLOSUM62, this
-    gives an asymmetric matrix, and a different PCA to a matrix produced
-    with the method described in the paper by G. Casari, C. Sander and
-    A. Valencia. Structural Biology volume 2, no. 2, February 1995 (<a
-      href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=7749921">pubmed</a>)
-    and implemented at the SeqSpace server at the EBI. This method
-    preconditions the matrix by multiplying it with its transpose, and
-    can be employed in the PCA viewer by unchecking the <strong><em>Jalview
-        PCA Calculation</em></strong> option in the <strong><em>Change
-        Parameters</em></strong> menu.
+      nucleotide substitution matrix</a>, or by sequence percentage identity,
+      or sequence feature similarity. 
   </p>
   <img src="pcaviewer.gif">
   <p>
@@ -89,8 +78,10 @@
     within the similarity space, as points in a rotateable 3D
     scatterplot. The colour of each sequence point is the same as the
     sequence group colours, white if no colour has been defined for the
-    sequence, and green if the sequence is part of a the currently
-    selected group.</p>
+    sequence, and grey if the sequence is part of the currently selected
+    group. The viewer also employs depth cueing, so points appear darker
+    the farther away they are, and become brighter as they are rotated
+    towards the front of the view.</p>
   <p>
     The 3d view can be rotated by dragging the mouse with the <strong>left
       mouse button</strong> pressed. The view can also be zoomed in and out with
@@ -141,5 +132,26 @@ left-clicking and dragging the mouse over the display. -->
       added to the Jalview desktop in v2.7.</em> <em>The Reset button
       and Change Parameters menu were added in Jalview 2.8.</em> <em>Support
       for PAM250 based PCA was added in Jalview 2.8.1.</em>
+  </p>
+  <p>
+    <strong>Reproducing PCA calculations performed with older
+      Jalview releases</strong> Jalview 2.10.2 included a revised PCA
+    implementation which treated Gaps and non-standard residues in the
+    same way as a matrix produced with the method described in the paper
+    by G. Casari, C. Sander and A. Valencia. Structural Biology volume
+    2, no. 2, February 1995 (<a
+      href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=7749921">pubmed</a>)
+    and implemented at the SeqSpace server at the EBI. To reproduce
+    calculations performed with earlier Jalview releases it is necessary
+    to execute the following Groovy script:
+  <pre>
+    jalview.analysis.scoremodels.ScoreMatrix.scoreGapAsAny=true
+    jalview.analysis.scoremodels.ScoreModels.instance.BLOSUM62.@matrix[4][1]=3
+    </pre>
+  This script enables the legacy PCA mode where gaps were treated as
+  'X', and to modify the BLOSUM62 matrix so it is asymmetric for
+  mutations between C to R (this was a typo in the original Jalview
+  BLOSUM62 matrix which was fixed in 2.10.2).
+  </p>
 </body>
 </html>
