X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=help%2Fhtml%2Fcalculations%2Fpca.html;fp=help%2Fhtml%2Fcalculations%2Fpca.html;h=ba9dc30605a082ef5eeccd059be55c6d5e9a1a83;hb=3f73b03257d72cbdd8cbe8889a6fc4fcab747dd3;hp=49019a7ec2541b44b465fb4090c8b1992ef49f04;hpb=1b9fc500a75a38d7c4408d4b209384d5236911cc;p=jalview.git

diff --git a/help/html/calculations/pca.html b/help/html/calculations/pca.html
index 49019a7..ba9dc30 100755
--- a/help/html/calculations/pca.html
+++ b/help/html/calculations/pca.html
@@ -32,7 +32,8 @@ 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><strong>About PCA</strong>Principal components analysis is a technique for examining the
+<p><strong>About PCA</strong></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
@@ -52,26 +53,26 @@ of variation in the data set.</p>
 			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.<br /> Jalview allows
-		two types of PCA calculation. The default
-		<em><strong>Jalview PCA Calculation</strong></em> mode (indicated when
-		that option is ticked in the
-		<strong><em>Change Parameters</em></strong> menu) of the viewer
-		performs 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 one 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
+		<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. The original method
-		preconditions the matrix by multiplying it with its transpose, and
-		this mode is enabled by unchecking the
-		<strong><em>Jalview PCA Calculation</em></strong> option in the
-		<strong><em>Change Parameters</em></strong> menu.
+		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.
 	</p>
-<img src="pcaviewer.gif">
+	<img src="pcaviewer.gif">
 	<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