FSTruct: An FST‐based tool for measuring ancestry variation in inference of population structure. (20th July 2022)
- Record Type:
- Journal Article
- Title:
- FSTruct: An FST‐based tool for measuring ancestry variation in inference of population structure. (20th July 2022)
- Main Title:
- FSTruct: An FST‐based tool for measuring ancestry variation in inference of population structure
- Authors:
- Morrison, Maike L.
Alcala, Nicolas
Rosenberg, Noah A. - Abstract:
- Abstract: In model‐based inference of population structure from individual‐level genetic data, individuals are assigned membership coefficients in a series of statistical clusters generated by clustering algorithms. Distinct patterns of variability in membership coefficients can be produced for different groups of individuals, for example, representing different predefined populations, sampling sites or time periods. Such variability can be difficult to capture in a single numerical value; membership coefficient vectors are multivariate and potentially incommensurable across predefined groups, as the number of clusters over which individuals are distributed can vary among groups of interest. Further, two groups might share few clusters in common, so that membership coefficient vectors are concentrated on different clusters. We introduce a method for measuring the variability of membership coefficients of individuals in a predefined group, making use of an analogy between variability across individuals in membership coefficient vectors and variation across populations in allele frequency vectors. We show that in a model in which membership coefficient vectors in a population follow a Dirichlet distribution, the measure increases linearly with a parameter describing the variance of a specified component of the membership vector and does not depend on its mean. We apply the approach, which makes use of a normalized F ST statistic, to data on inferred population structure inAbstract: In model‐based inference of population structure from individual‐level genetic data, individuals are assigned membership coefficients in a series of statistical clusters generated by clustering algorithms. Distinct patterns of variability in membership coefficients can be produced for different groups of individuals, for example, representing different predefined populations, sampling sites or time periods. Such variability can be difficult to capture in a single numerical value; membership coefficient vectors are multivariate and potentially incommensurable across predefined groups, as the number of clusters over which individuals are distributed can vary among groups of interest. Further, two groups might share few clusters in common, so that membership coefficient vectors are concentrated on different clusters. We introduce a method for measuring the variability of membership coefficients of individuals in a predefined group, making use of an analogy between variability across individuals in membership coefficient vectors and variation across populations in allele frequency vectors. We show that in a model in which membership coefficient vectors in a population follow a Dirichlet distribution, the measure increases linearly with a parameter describing the variance of a specified component of the membership vector and does not depend on its mean. We apply the approach, which makes use of a normalized F ST statistic, to data on inferred population structure in three example scenarios. We also introduce a bootstrap test for equivalence of two or more predefined groups in their level of membership coefficient variability. Our methods are implemented in the r package FSTruct. … (more)
- Is Part Of:
- Molecular ecology resources. Volume 22:Number 7(2022)
- Journal:
- Molecular ecology resources
- Issue:
- Volume 22:Number 7(2022)
- Issue Display:
- Volume 22, Issue 7 (2022)
- Year:
- 2022
- Volume:
- 22
- Issue:
- 7
- Issue Sort Value:
- 2022-0022-0007-0000
- Page Start:
- 2614
- Page End:
- 2626
- Publication Date:
- 2022-07-20
- Subjects:
- FST -- admixture -- population structure
Molecular ecology -- Periodicals
572.8 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1755-0998 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/1755-0998.13647 ↗
- Languages:
- English
- ISSNs:
- 1755-098X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5900.817368
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 23330.xml