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- * Jalview - A Sequence Alignment Editor and Viewer (Version 2.5)
- * Copyright (C) 2010 J Procter, AM Waterhouse, G Barton, M Clamp, S Searle
+ * Jalview - A Sequence Alignment Editor and Viewer (Version 2.7)
+ * Copyright (C) 2011 J Procter, AM Waterhouse, J Engelhardt, LM Lui, G Barton, M Clamp, S Searle
*
* This file is part of Jalview.
*
*
* You should have received a copy of the GNU General Public License along with Jalview. If not, see <http://www.gnu.org/licenses/>.
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+<head>
+<title>Principal Component Analysis</title>
+</head>
+<body>
+<p><strong>Principal Component Analysis</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>Note: 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.</p>
+<p>Principal components analysis is a technique for examining the
+structure of complex data sets. The components are a set of dimensions
+formed from the measured values in the data set, and the principle
+component is the one with the greatest magnitude, or length. The sets of
+measurements that differ the most should lie at either end of this
+principle axis, and the other axes correspond to less extreme patterns
+of variation in the data set.</p>
+
+<p>In this case, the components are generated by an eigenvector
+decomposition of the matrix formed from the sum of BLOSUM scores at each
+aligned position between each pair of sequences. The matrix is not
+symmetric - 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. This is a refinement of 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.</p>
+
+<p><strong>The PCA Viewer</strong></p>
+<p>This is an interactive display of the sequences positioned 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>
+<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 the up
+and down <strong>arrow keys</strong> (and the roll bar of the mouse if
+present). Labels will be shown for each sequence if the entry in the
+View menu is checked, and the plot background colour changed from the
+View→Background Colour.. dialog box. The File menu allows the view
+to be saved (<strong>File→Save</strong> submenu) as an EPS or PNG
+image or printed, and the original alignment data and matrix resulting
+from its PCA analysis to be retrieved. The coordinates for the whole PCA
+space, or just the current view may also be exported as CSV files for
+visualization in another program or further analysis.</p>
+<p>A tool tip gives the sequence ID corresponding to a point in the
+space, and clicking a point toggles the selection of the corresponding
+sequence in the associated alignment window views. Rectangular region
+based selection is also possible, by holding the 'S' key whilst
+left-clicking and dragging the mouse over the display. By default,
+points are only associated with the alignment view from which the PCA
+was calculated, but this may be changed via the <strong>View→Associate
+Nodes</strong> sub-menu.</p>
+<p>Initially, the display shows the first three components of the
+similarity space, but any eigenvector can be used by changing the
+selected dimension for the x, y, or z axis through each ones menu
+located below the 3d display.</p>
+<p>
+<p>
+</body>
+</html>
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