Abstract
Fundamental to Multiple Sequence Alignment (MSA) algorithms is modelling insertions and deletions (gaps). The most prevalent model is to use Gap Open Penalties (GOP) and Gap Extension Penalties (GEP). While GOP and GEP are well understood conceptually, their effects on MSA and consequently on phylogeny scores are not as well understood. We use exhaustive phylogeny searching to explore the effects of varying the GOP and GEP for three nuclear ribosomal data sets. Particular attention is given to optimal maximum likelihood and parsimony phylogeny scores for various alignments of a range of GOP and GEP and their respective distribution of phylogeny scores.
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