Emmanuel wrote:
Is it a problem with ties or with identical sequences? I guess you can
solve the latter easily (eg, using the haplotype function in
pegas), and
this will solve the vast majority of ties. Other cases of ties will
certainly not result in such high bootstrap values (that's my
Hi Emmanuel (Klaus and Joe),
The example data was meant to demonstrate that the tie-breaking in nj is
affecting the bootstrap results - or rather the lack of any way to deal
with tie breaking.
I've noticed that a bunch of identical sequences form a 'polytomy' in my
real dataset (but obviously
Hi Alastair, Klaus Joe,
Before doing the tree, you should do some preliminary data explorations,
such as:
d - dist.dna(a)
hist(d)
summary(d)
That'd show you any tree estimation procedure (not only NJ) has very
little meaning -- just like you do plot(x, y) before doing lm(y ~ x).
Best,
Hi Alastair,
it is not that surprising. NJ normally does not produce poytomies,
just edge weights of length 0. How these are broken may depends from
the input order (from labels in the distance matrix like in this
implementation) or could be broken randomly. I added some code below
to highlight
