Abstract
In this study, we present a novel methodology to infer indel parameters from multiple sequence alignments (MSAs) based on simulations. Our algorithm searches for the set of evolutionary parameters describing indel dynamics which best fits a given input MSA. In each step of the search, we use parametric bootstraps and the Mahalanobis distance to estimate how well a proposed set of parameters fits input data. Using simulations, we demonstrate that our methodology can accurately infer the indel parameters for a large variety of plausible settings. Moreover, using our methodology, we show that indel parameters substantially vary between three genomic data sets: Mammals, bacteria, and retroviruses. Finally, we demonstrate how our methodology can be used to simulate MSAs based on indel parameters inferred from real data sets.
Original language | English (US) |
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Pages (from-to) | 3226-3238 |
Number of pages | 13 |
Journal | Genome biology and evolution |
Volume | 7 |
Issue number | 12 |
DOIs | |
State | Published - Dec 2015 |
Keywords
- Alignments
- Indels
- Mahalanobis distance
- Phylogeny
- Simulations
ASJC Scopus subject areas
- General Medicine