On the prospect of achieving accurate joint estimation of selection with population history
Affiliation
Department of Molecular and Cellular Biology, University of ArizonaIssue Date
2022Keywords
background selectiondemography
genetic hitchhiking
natural selection
population history
statistical inference
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Oxford University PressCitation
Johri, P., Eyre-Walker, A., Gutenkunst, R. N., Lohmueller, K. E., & Jensen, J. D. (2022). On the prospect of achieving accurate joint estimation of selection with population history. Genome Biology and Evolution, 14(7).Journal
Genome biology and evolutionRights
Copyright © The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
As both natural selection and population history can affect genome-wide patterns of variation, disentangling the contributions of each has remained as a major challenge in population genetics. We here discuss historical and recent progress towards this goal-highlighting theoretical and computational challenges that remain to be addressed, as well as inherent difficulties in dealing with model complexity and model violations-and offer thoughts on potentially fruitful next steps. © The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.Note
Open access journalISSN
1759-6653PubMed ID
35675379Version
Final published versionScopus Count
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Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/).