From: James Procter Date: Wed, 15 Nov 2023 11:48:30 +0000 (+0000) Subject: JAL-4090 JAL-3858 fix up PAE docs - drop the EBI image example X-Git-Tag: Release_2_11_3_0~1^2~4 X-Git-Url: http://source.jalview.org/gitweb/?p=jalview.git;a=commitdiff_plain;h=181fd0fa4064654d94f76c3f4ff9333f0ea1834b JAL-4090 JAL-3858 fix up PAE docs - drop the EBI image example --- diff --git a/help/help/html/features/paematrices.html b/help/help/html/features/paematrices.html index 2f00e19..8857894 100644 --- a/help/help/html/features/paematrices.html +++ b/help/help/html/features/paematrices.html @@ -29,13 +29,14 @@ Jalview

-

Predicted Alignment Error (PAE) matrices are produced by - deep-learning based 3D-structure prediction pipelines such as - AlphaFold. They reflect how reliably two parts of a model have been - positioned in space, by giving for each residue the likely error (in - Ångstroms) between that residue and every other modelled - position the pair of residues' real relative position, if the model - and real 3D structure were superimposed at that residue.

+

Predicted Alignment Error (PAE) matrices are produced by + deep-learning based 3D-structure prediction pipelines such as + AlphaFold. They reflect how reliably two parts of a model have been + positioned in space. Each column in a PAE matrix corresponds to a + residue in the model, and each gives the likely RMS error (in + Ångstroms) between that residue and every other modelled + position the pair of residues' real relative position, if the model + and real 3D structure were superimposed at that residue.

Jalview visualises PAE matrices as an alignment annotation track, shaded from dark green to white, similar to the encoding used on the @@ -43,23 +44,22 @@ href="https://alphafold.ebi.ac.uk/entry/O04090">O04090 3D model at EBI-AlphaFoldDB).

-
+ +
+ Alignment of EPAS1 homologs from Human, Rat and Cow shaded by PLDDT, with + Predicted Alignment Error and secondary structure annotation shown for Human. + +

Importing PAE Matrices

@@ -76,9 +76,9 @@

The Command Line - Interface also provides a options for importing PAE matrices along - side models, enabling the automated production of alignment figures - annotated with PAE matrices and PLDDT scores. + Interface also provides the option to import a PAE matrix alongside + a 3D structure file, enabling the automated production of alignment figures + annotated with PAE matrices and PLDDT scores.

Showing PAE Matrix Annotations @@ -86,7 +86,7 @@

When viewing 3D structures from the EBI-AlphaFold database or local 3D structures with an associated PAE file, the PAE is imported as Reference - Annotation, which is not always automatically added to the alignment + Annotation, and is not always automatically added to the alignment view.

To show the PAE, right click the sequence and locate the 'Add @@ -136,9 +136,9 @@ PAE often correlate with high alphafold reliability (PLDDT) scores, but also complement them since they highlight well-folded regions such as domains, and how well those regions have been predicted to be - positioned relative to eachother, which is important when evaluating + positioned relative to each other, which is important when evaluating whether domain-domain interactions or other contacts can be trusted.

-

To make it more easy to identify regions of low PAE, Jalview can +

To make it easy to identify regions of low PAE, Jalview can cluster the PAE matrix, allowing columns of the matrix to be grouped according to their similarity, using an Average Distance (UPGMA) tree algorithm and the sum of differences between each column's PAE values.

@@ -147,25 +147,28 @@ ∥

- To create a PAE matrix tree, right click on a PAE annotation's label + Creating a PAE matrix tree
Right click on a PAE annotation's label to open the annotation popup menu, and select Cluster Matrix. Once the calculation has finished, a tree viewer will open, and columns of the matrix are then partitioned into groups such that the third left-most node from the root is placed in its own group. - Colours are randomly assigned to each group, and by default these will - also be overlaid on the matrix annotation row. + Colours are randomly assigned to each group. By default column group colours will + also be overlaid on the matrix annotation row - this can be turned off + via the PAE annotation row menu (by unticking Show groups on matrix).

+ The PAE matrix tree viewer behaves like other tree views, except:

+ Once the PAE annotation has clustering defined: +