Sequences sorting in labs

If I’m not mistaken, sequences in labs can be sorted, and the algorithm currently in use seems to be the Hamming distance.

I’d like to propose a new sorting algorithm (which I dubbed “LDq9”), based on a Lee distance metric with a pseudo-alphabet of size 9 (or more). An example mapping would be:


Which would result in following specific distances:

A:G = 1
U:C = 1

G:C = 4
G:U = 3
A:U = 4
A:C = 4

The basic idea simply being that, changes within the same nucleotide classes (purines or pyrimidines) represent a short distance, while a change of class represent a larger jump.

I believe that this would give a somewhat better view of the similarity of sequences, specially in the context of switches.

Nice idea.

Hmm. Suppose I change a GC bond to CG. How does that get scored? And should it differ if it’s a switch lab or not?

GC to CG would be a +8 step.
I don’t think the metric should change between static labs and switch ones, but this idea of mine may prove making little difference with a simple Hamming in the case of static target structures.
For switches, I’m almost convinced that this sorting would be a lot more accurate.

Worth a try if the coding isn’t too much.