Alignment Quality Annotation
-Alignment Quality is one of the automatically calculated -quantitative alignment -annotations displayed below the columns of a multiple sequence -alignment (and can be used to shade the alignment). It is an ad-hoc -measure of the likelihood of observing the mutations (if any) in a -particular column of the alignment.
--More precisely, the quality score is inversely proportional to the -average cost of all pairs of mutations observed in a particular column -of the alignment - a high alignment quality score for a column would -suggest that there are no mutations, or most mutations observed are -favourable. -
++ Alignment Quality Annotation +
+Alignment Quality is one of the automatically calculated + quantitative alignment annotations displayed below the columns of a + multiple sequence alignment (and can be used to shade the + alignment). It is an ad-hoc measure of the likelihood of observing + the mutations (if any) in a particular column of the alignment.
+More precisely, the quality score is inversely proportional to + the average cost of all pairs of mutations observed in a particular + column of the alignment - a high alignment quality score for a + column would suggest that there are no mutations, or most mutations + observed are favourable.
-The Algorithm
-The quality score is calculated for each column in an alignment by
-summing, for all mutations, the ratio of the two BLOSUM 62 scores for
-a mutation pair and each residue's conserved BLOSUM62 score (which
-is higher). This value is normalised for each column, and then plotted
-on a scale from 0 to 1.
-
-Multiple alignment algorithms using the BLOSUM 62 substition matrices -should, in theory, maximise alignment quality for an un-gapped -alignment, and locally maximise quality for gapped alignments. -
+
+ The Algorithm
The quality score is calculated for
+ each column in an alignment by summing, for all mutations, the ratio
+ of the two BLOSUM 62 scores for a mutation pair and each residue's
+ conserved BLOSUM62 score (which is higher). This value is normalised
+ for each column, and then plotted on a scale from 0 to 1.
+
Multiple alignment algorithms using the BLOSUM 62 substitution + matrices should, in theory, maximise alignment quality for an + un-gapped alignment, and locally maximise quality for gapped + alignments.