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Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty

BACKGROUND: Multiple sequence alignments (MSAs) represent the fundamental unit of data inputted to most comparative sequence analyses. In phylogenetic analyses in particular, errors in MSA construction have the potential to induce further errors in downstream analyses such as phylogenetic reconstruc...

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Autores principales: Spielman, Stephanie J., Miraglia, Molly L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628390/
https://www.ncbi.nlm.nih.gov/pubmed/34844571
http://dx.doi.org/10.1186/s12862-021-01931-5
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author Spielman, Stephanie J.
Miraglia, Molly L.
author_facet Spielman, Stephanie J.
Miraglia, Molly L.
author_sort Spielman, Stephanie J.
collection PubMed
description BACKGROUND: Multiple sequence alignments (MSAs) represent the fundamental unit of data inputted to most comparative sequence analyses. In phylogenetic analyses in particular, errors in MSA construction have the potential to induce further errors in downstream analyses such as phylogenetic reconstruction itself, ancestral state reconstruction, and divergence time estimation. In addition to providing phylogenetic methods with an MSA to analyze, researchers must also specify a suitable evolutionary model for the given analysis. Most commonly, researchers apply relative model selection to select a model from candidate set and then provide both the MSA and the selected model as input to subsequent analyses. While the influence of MSA errors has been explored for most stages of phylogenetics pipelines, the potential effects of MSA uncertainty on the relative model selection procedure itself have not been explored. RESULTS: We assessed the consistency of relative model selection when presented with multiple perturbed versions of a given MSA. We find that while relative model selection is mostly robust to MSA uncertainty, in a substantial proportion of circumstances, relative model selection identifies distinct best-fitting models from different MSAs created from the same set of sequences. We find that this issue is more pervasive for nucleotide data compared to amino-acid data. However, we also find that it is challenging to predict whether relative model selection will be robust or sensitive to uncertainty in a given MSA. CONCLUSIONS: We find that that MSA uncertainty can affect virtually all steps of phylogenetic analysis pipelines to a greater extent than has previously been recognized, including relative model selection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12862-021-01931-5.
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spelling pubmed-86283902021-12-01 Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty Spielman, Stephanie J. Miraglia, Molly L. BMC Ecol Evol Research BACKGROUND: Multiple sequence alignments (MSAs) represent the fundamental unit of data inputted to most comparative sequence analyses. In phylogenetic analyses in particular, errors in MSA construction have the potential to induce further errors in downstream analyses such as phylogenetic reconstruction itself, ancestral state reconstruction, and divergence time estimation. In addition to providing phylogenetic methods with an MSA to analyze, researchers must also specify a suitable evolutionary model for the given analysis. Most commonly, researchers apply relative model selection to select a model from candidate set and then provide both the MSA and the selected model as input to subsequent analyses. While the influence of MSA errors has been explored for most stages of phylogenetics pipelines, the potential effects of MSA uncertainty on the relative model selection procedure itself have not been explored. RESULTS: We assessed the consistency of relative model selection when presented with multiple perturbed versions of a given MSA. We find that while relative model selection is mostly robust to MSA uncertainty, in a substantial proportion of circumstances, relative model selection identifies distinct best-fitting models from different MSAs created from the same set of sequences. We find that this issue is more pervasive for nucleotide data compared to amino-acid data. However, we also find that it is challenging to predict whether relative model selection will be robust or sensitive to uncertainty in a given MSA. CONCLUSIONS: We find that that MSA uncertainty can affect virtually all steps of phylogenetic analysis pipelines to a greater extent than has previously been recognized, including relative model selection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12862-021-01931-5. BioMed Central 2021-11-29 /pmc/articles/PMC8628390/ /pubmed/34844571 http://dx.doi.org/10.1186/s12862-021-01931-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Spielman, Stephanie J.
Miraglia, Molly L.
Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty
title Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty
title_full Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty
title_fullStr Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty
title_full_unstemmed Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty
title_short Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty
title_sort relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628390/
https://www.ncbi.nlm.nih.gov/pubmed/34844571
http://dx.doi.org/10.1186/s12862-021-01931-5
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