Dear Sergei,

I have programmed Felsenstein's pruning algorithm as an exercise in Python and get the same likelihood for a tree with fixed parameters as HyPhy, except when the codon/nucleotide at a site is unknown for one or more sequences.

I was just wondering how HyPhy handles such unknown nucleotides/codons in the initialization of the pruning algorithm. For example, if the nucleotide at a site is, say, cytosine and sites are ordered [A,C,G,T], then the conditional likelihoods at the tip of the tree are initialized as [0,1,0,0] in the pruning algorithm. When the nucleotide is unknown, is the initialization [1,1,1,1] or [0.25,0.25,0.25,0.25]? Although, you should arrive at the same MLEs either way, the maximum value of the likelihood function will differ. What does HyPhy do?

Thanks in advance,
Miguel