ArticleGenome biology and evolution2015
Inferring Indel Parameters using a Simulation-based Approach.
Article in Genome biology and evolution, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Insertions and Deletions: Computational Methods, Evolutionary Dynamics, and Biological Applications.Molecular biology and evolution · 2024Review
- A Probabilistic Model for Indel Evolution: Differentiating Insertions from Deletions.Molecular biology and evolution · 2021Article
- The Evolutionary Traceability of a Protein.Genome biology and evolution · 2019Article
- Alignment Modulates Ancestral Sequence Reconstruction Accuracy.Molecular biology and evolution · 2018Article
- Inferring Rates and Length-Distributions of Indels Using Approximate Bayesian Computation.Genome biology and evolution · 2017Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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