Seth Sullivant : Statistically-Consistent k-mer Methods for Phylogenetic Tree Reconstruction (Oct 7, 2016 11:55 AM)
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 the corrected distance out-performs 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. This is joint work with Elizabeth Allman and John Rhodes.
- Category: Mathematical Biology
- Duration: 01:34:48
- Date: October 7, 2016 at 11:55 AM
- Views: 166
- Tags: seminar, Mathematical Biology Seminar
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