Principal Component Analysis
-A principal component analysis can be performed via the - calculations dialog which is accessed by selecting Calculate→Calculate - Tree or PCA....
++ A principal component analysis can be performed via the calculations dialog which is accessed + by selecting Calculate→Calculate Tree or + PCA.... +
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
@@ -57,33 +60,15 @@
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,
+ eigenvector decomposition of the matrix formed from pairwise similarity
+ scores between each pair of sequences. The similarity score model is
+ selected on the calculations dialog, and
+ may use 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.
+ nucleotide substitution matrix, or by sequence percentage identity,
+ or sequence feature similarity.
@@ -145,5 +130,26 @@ left-clicking and dragging the mouse over the display. --> 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. +
++ Reproducing PCA calculations performed with older + Jalview releases 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 (pubmed) + 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: +
+ jalview.analysis.scoremodels.ScoreMatrix.scoreGapAsAny=true + jalview.analysis.scoremodels.ScoreModels.instance.BLOSUM62.@matrix[4][1]=3 ++ 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). +