2026-05-25T21:17:38Zhttps://keep.lib.asu.edu/oai/requestoai:keep.lib.asu.edu:node-1284702025-09-16T16:34:45Zoai_pmh:alloai_pmh:repo_items128470
https://hdl.handle.net/2286/R.I.44470
<p>Karin, E. L., Rabin, A., Ashkenazy, H., Shkedy, D., Avram, O., Cartwright, R. A., & Pupko, T. (2015). Inferring Indel Parameters using a Simulation-based Approach. Genome Biology and Evolution, 7(12), 3226-3238. doi:10.1093/gbe/evv212</p>
10.1093/gbe/evv212
1759-6653
http://rightsstatements.org/vocab/InC/1.0/
open access
http://creativecommons.org/licenses/by/4.0
2015-11-03
13 pages
eng
Levy Karin, Eli
Rabin, Avigayel
Ashkenazy, Haim
Shkedy, Dafna
Avram, Oren
Cartwright, Reed
Pupko, Tal
Biodesign Institute
The final version of this article, as published in Genome Biology and Evolution, can be viewed online at: https://academic.oup.com/gbe/article/7/12/3226/2466039/Inferring-Indel-Parameters-using-a-Simulation
<p>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.</p>
Text
Inferring Indel Parameters Using a Simulation-Based Approach