X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=help%2Fhtml%2Fcalculations%2Fpca.html;h=8d6f329041cae2459af19ae9f326780a00e022aa;hb=911c6630cec6fa5253821a7e18a13d0d4df3627c;hp=8cbf0ca8cb41a30a475ca090485865c28076285a;hpb=96b6991703b70a1bbb0491f9946d397c9fcf5a38;p=jalview.git diff --git a/help/html/calculations/pca.html b/help/html/calculations/pca.html index 8cbf0ca..8d6f329 100755 --- a/help/html/calculations/pca.html +++ b/help/html/calculations/pca.html @@ -1,4 +1,24 @@ +
Note: The calculation is computationally expensive, and may fail +
Caveats
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.
About PCA
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 @@ -21,15 +43,39 @@ 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.
-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 basic method is -described in the paper by G. Casari, C. Sander and A. Valencia. -Structural Biology volume 2, no. 2, February 1995 (pubmed) -and implemented at the SeqSpace server at the EBI.
- -The PCA Viewer
+
+ Calculating PCAs for aligned sequences
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
+ BLOSUM62, PAM250, or the simple single
+ nucleotide substitution matrix. The options available for
+ calculation are given in the
+ Change Parameters menu.
+ PCA Calculation modes
+ The default Jalview calculation mode
+ (indicated when Jalview PCA Calculation is
+ ticked in the Change Parameters 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 (pubmed)
+ 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 Jalview
+ PCA Calculation option in the Change
+ Parameters menu.
+
The PCA Viewer
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, @@ -43,19 +89,31 @@ 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 (File→Save submenu) as an EPS or PNG image or printed, and the original alignment data and matrix resulting -from its PCA analysis to be retrieved.
+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.+
Options for coordinates export are:
+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 +sequence in the associated alignment window views. By default, points are only associated with the alignment view from which the PCA -was calculated, but this may be changed via the Associate +was calculated, but this may be changed via the View→Associate Nodes sub-menu.
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.
+located below the 3d display. The Reset button will reset axis and rotation settings to their defaults. +
+The output of points and transformed point coordinates was added to the Jalview desktop in v2.7. +The Reset button and Change Parameters menu were added in Jalview 2.8. +Support for PAM250 based PCA was added in Jalview 2.8.1.