Inferring indel parametersusing a simulation-based approach

Eli Levy Karin, Avigayel Rabin, Haim Ashkenazy, Dafna Shkedy, Oren Avram, Reed A. Cartwright, Tal Pupko

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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 languageEnglish (US)
Pages (from-to)3226-3238
Number of pages13
JournalGenome biology and evolution
Issue number12
StatePublished - Dec 2015


  • Alignments
  • Indels
  • Mahalanobis distance
  • Phylogeny
  • Simulations

ASJC Scopus subject areas

  • General Medicine


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