Discrete
all characters are known, nothing in between
Distance
simpler, no ins/del
ex. minimum evolution, goodniss of fit (additive)
1. distance loses information
Advantages?
distance is quicker
1. closer to original data with fewer steps
2. can map traits dirrectlt to different branches where mutations occur + know type of mutation
Earliest forms of distance
allozyme and microsatellite
Additive tree
shows amount of change
no root, indicates branching pattern ?
Ultametric tree
shows number of mutations
proportional to temporal distance (time?)
Clustering
"recipe"
step by step to final tree, same or small set of outcomes
reaches an answer
Optimality
very very best method "best apple pie" lol
more time and investment
close to best answer
1. explicit measure of data/tree
2. compares different hypotheses
evaluate every phylogeny to find best one (optimal topology)
Neighbor joining + steps
begin w/ distance matrix
group 2 taxa w/ shortest distance
create new node
calculate distance of each included taxon to new node
recalculate distance matrix using new node
repeat
Parsimony
simple = best
discrete, optimality
im assuming in strict parsimony all characters are treated equally
similar to JC Jukes-cantor model of evolution since all mutations are the same.
Autapomorphy
?? do we need to know this
Heuristic search?
swapping pruning and bisection
random additions