  Phylogenetic analyses based on small to moderately sized sets of sequential
data lead to overestimating mutation rates in influenza hemagglutinin (HA) by
at least an order of magnitude. Two major underlying reasons are: the
incomplete lineage sorting, and a possible absence in the analyzed sequences
set some of key missing ancestors. Additionally, during neighbor joining tree
reconstruction each mutation is considered equally important, regardless of its
nature. Here we have implemented a heuristic method optimizing site dependent
factors weighting differently 1st, 2nd, and 3rd codon position mutations,
allowing to extricate incorrectly attributed sub-clades. The least squares
regression analysis of distribution of frequencies for all mutations observed
on a partially disentangled tree for a large set of unique 3243 HA sequences,
along all nucleotide positions, was performed for all mutations as well as for
non-equivalent amino acid mutations: in both cases demonstrating almost flat
gradients, with a very slight downward slope towards the 3'-end positions. The
mean mutation rates per sequence per year were 3.83*10^-4 for the all
mutations, and 9.64*10^-5 for the non-equivalent ones.
