Simulation of Finnish population history, guided by empirical genetic data, to assess power of rare-variant tests in Finland
(2014) In American Journal of Human Genetics 94(5). p.20-710- Abstract
Finnish samples have been extensively utilized in studying single-gene disorders, where the founder effect has clearly aided in discovery, and more recently in genome-wide association studies of complex traits, where the founder effect has had less obvious impacts. As the field starts to explore rare variants' contribution to polygenic traits, it is of great importance to characterize and confirm the Finnish founder effect in sequencing data and to assess its implications for rare-variant association studies. Here, we employ forward simulation, guided by empirical deep resequencing data, to model the genetic architecture of quantitative polygenic traits in both the general European and the Finnish populations simultaneously. We... (More)
Finnish samples have been extensively utilized in studying single-gene disorders, where the founder effect has clearly aided in discovery, and more recently in genome-wide association studies of complex traits, where the founder effect has had less obvious impacts. As the field starts to explore rare variants' contribution to polygenic traits, it is of great importance to characterize and confirm the Finnish founder effect in sequencing data and to assess its implications for rare-variant association studies. Here, we employ forward simulation, guided by empirical deep resequencing data, to model the genetic architecture of quantitative polygenic traits in both the general European and the Finnish populations simultaneously. We demonstrate that power of rare-variant association tests is higher in the Finnish population, especially when variants' phenotypic effects are tightly coupled with fitness effects and therefore reflect a greater contribution of rarer variants. SKAT-O, variable-threshold tests, and single-variant tests are more powerful than other rare-variant methods in the Finnish population across a range of genetic models. We also compare the relative power and efficiency of exome array genotyping to those of high-coverage exome sequencing. At a fixed cost, less expensive genotyping strategies have far greater power than sequencing; in a fixed number of samples, however, genotyping arrays miss a substantial portion of genetic signals detected in sequencing, even in the Finnish founder population. As genetic studies probe sequence variation at greater depth in more diverse populations, our simulation approach provides a framework for evaluating various study designs for gene discovery.
(Less)
- author
- Wang, Sophie R ; Agarwala, Vineeta ; Flannick, Jason ; Chiang, Charleston W K ; Altshuler, David and Hirschhorn, Joel N
- contributor
- Kravic, Jasmina LU
- author collaboration
- organization
- publishing date
- 2014-05-01
- type
- Contribution to journal
- publication status
- published
- keywords
- Computer Simulation, Diabetes Mellitus, Type 2/genetics, European Continental Ancestry Group/genetics, Exome/genetics, Finland, Founder Effect, Humans, Models, Genetic, Multifactorial Inheritance/genetics, Population/genetics
- in
- American Journal of Human Genetics
- volume
- 94
- issue
- 5
- pages
- 11 pages
- publisher
- Cell Press
- external identifiers
-
- pmid:24768551
- scopus:84899921864
- ISSN
- 0002-9297
- DOI
- 10.1016/j.ajhg.2014.03.019
- language
- English
- LU publication?
- yes
- id
- b2639d36-4b1b-46e6-bc3f-47a4145205e5
- date added to LUP
- 2019-01-21 10:15:29
- date last changed
- 2024-06-11 02:55:17
@article{b2639d36-4b1b-46e6-bc3f-47a4145205e5,
abstract = {{<p>Finnish samples have been extensively utilized in studying single-gene disorders, where the founder effect has clearly aided in discovery, and more recently in genome-wide association studies of complex traits, where the founder effect has had less obvious impacts. As the field starts to explore rare variants' contribution to polygenic traits, it is of great importance to characterize and confirm the Finnish founder effect in sequencing data and to assess its implications for rare-variant association studies. Here, we employ forward simulation, guided by empirical deep resequencing data, to model the genetic architecture of quantitative polygenic traits in both the general European and the Finnish populations simultaneously. We demonstrate that power of rare-variant association tests is higher in the Finnish population, especially when variants' phenotypic effects are tightly coupled with fitness effects and therefore reflect a greater contribution of rarer variants. SKAT-O, variable-threshold tests, and single-variant tests are more powerful than other rare-variant methods in the Finnish population across a range of genetic models. We also compare the relative power and efficiency of exome array genotyping to those of high-coverage exome sequencing. At a fixed cost, less expensive genotyping strategies have far greater power than sequencing; in a fixed number of samples, however, genotyping arrays miss a substantial portion of genetic signals detected in sequencing, even in the Finnish founder population. As genetic studies probe sequence variation at greater depth in more diverse populations, our simulation approach provides a framework for evaluating various study designs for gene discovery. </p>}},
author = {{Wang, Sophie R and Agarwala, Vineeta and Flannick, Jason and Chiang, Charleston W K and Altshuler, David and Hirschhorn, Joel N}},
issn = {{0002-9297}},
keywords = {{Computer Simulation; Diabetes Mellitus, Type 2/genetics; European Continental Ancestry Group/genetics; Exome/genetics; Finland; Founder Effect; Humans; Models, Genetic; Multifactorial Inheritance/genetics; Population/genetics}},
language = {{eng}},
month = {{05}},
number = {{5}},
pages = {{20--710}},
publisher = {{Cell Press}},
series = {{American Journal of Human Genetics}},
title = {{Simulation of Finnish population history, guided by empirical genetic data, to assess power of rare-variant tests in Finland}},
url = {{http://dx.doi.org/10.1016/j.ajhg.2014.03.019}},
doi = {{10.1016/j.ajhg.2014.03.019}},
volume = {{94}},
year = {{2014}},
}