Abstract Frequencies of k-mers in sequences are sometimes used as a basis for inferring phylogenetic trees without first obtaining a multiple sequence alignment. We show that a standard approach of using the squared Euclidean distance between k-mer vectors to approximate a tree metric can be statistically inconsistent. To remedy this, we derive model-based distance corrections for orthologous sequences without gaps, which lead to consistent tree inference. The identifiability of model parameters from k-mer frequencies is also studied. Finally, we report simulations showing that the corrected distance outperforms many other k-mer methods, even when sequences are generated with an insertion and deletion process. These results have implications for multiple sequence alignment as well since k-mer methods are usually the first step in constructing a guide tree for such algorithms." /> rel="meta" type="application/atom+xml" href="http://dx.doi.org/10.1089%2Fcmb.2015.0216" /> rel="meta" type="application/rdf+json" href="http://dx.doi.org/10.1089%2Fcmb.2015.0216" /> rel="meta" type="application/unixref+xml" href="http://dx.doi.org/10.1089%2Fcmb.2015.0216" /> 展开▼
