Cargando…
Identifying consistent allele frequency differences in studies of stratified populations
1. With increasing application of pooled‐sequencing approaches to population genomics robust methods are needed to accurately quantify allele frequency differences between populations. Identifying consistent differences across stratified populations can allow us to detect genomic regions under selec...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5726381/ https://www.ncbi.nlm.nih.gov/pubmed/29263778 http://dx.doi.org/10.1111/2041-210X.12810 |
_version_ | 1783285712238411776 |
---|---|
author | Wiberg, R. Axel W. Gaggiotti, Oscar E. Morrissey, Michael B. Ritchie, Michael G. |
author_facet | Wiberg, R. Axel W. Gaggiotti, Oscar E. Morrissey, Michael B. Ritchie, Michael G. |
author_sort | Wiberg, R. Axel W. |
collection | PubMed |
description | 1. With increasing application of pooled‐sequencing approaches to population genomics robust methods are needed to accurately quantify allele frequency differences between populations. Identifying consistent differences across stratified populations can allow us to detect genomic regions under selection and that differ between populations with different histories or attributes. Current popular statistical tests are easily implemented in widely available software tools which make them simple for researchers to apply. However, there are potential problems with the way such tests are used, which means that underlying assumptions about the data are frequently violated. 2. These problems are highlighted by simulation of simple but realistic population genetic models of neutral evolution and the performance of different tests are assessed. We present alternative tests (including Generalised Linear Models [GLMs] with quasibinomial error structure) with attractive properties for the analysis of allele frequency differences and re‐analyse a published dataset. 3. The simulations show that common statistical tests for consistent allele frequency differences perform poorly, with high false positive rates. Applying tests that do not confound heterogeneity and main effects significantly improves inference. Variation in sequencing coverage likely produces many false positives and re‐scaling allele frequencies to counts out of a common value or an effective sample size reduces this effect. 4. Many researchers are interested in identifying allele frequencies that vary consistently across replicates to identify loci underlying phenotypic responses to selection or natural variation in phenotypes. Popular methods that have been suggested for this task perform poorly in simulations. Overall, quasibinomial GLMs perform better and also have the attractive feature of allowing correction for multiple testing by standard procedures and are easily extended to other designs. |
format | Online Article Text |
id | pubmed-5726381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57263812017-12-18 Identifying consistent allele frequency differences in studies of stratified populations Wiberg, R. Axel W. Gaggiotti, Oscar E. Morrissey, Michael B. Ritchie, Michael G. Methods Ecol Evol Evolutionary Biology 1. With increasing application of pooled‐sequencing approaches to population genomics robust methods are needed to accurately quantify allele frequency differences between populations. Identifying consistent differences across stratified populations can allow us to detect genomic regions under selection and that differ between populations with different histories or attributes. Current popular statistical tests are easily implemented in widely available software tools which make them simple for researchers to apply. However, there are potential problems with the way such tests are used, which means that underlying assumptions about the data are frequently violated. 2. These problems are highlighted by simulation of simple but realistic population genetic models of neutral evolution and the performance of different tests are assessed. We present alternative tests (including Generalised Linear Models [GLMs] with quasibinomial error structure) with attractive properties for the analysis of allele frequency differences and re‐analyse a published dataset. 3. The simulations show that common statistical tests for consistent allele frequency differences perform poorly, with high false positive rates. Applying tests that do not confound heterogeneity and main effects significantly improves inference. Variation in sequencing coverage likely produces many false positives and re‐scaling allele frequencies to counts out of a common value or an effective sample size reduces this effect. 4. Many researchers are interested in identifying allele frequencies that vary consistently across replicates to identify loci underlying phenotypic responses to selection or natural variation in phenotypes. Popular methods that have been suggested for this task perform poorly in simulations. Overall, quasibinomial GLMs perform better and also have the attractive feature of allowing correction for multiple testing by standard procedures and are easily extended to other designs. John Wiley and Sons Inc. 2017-06-15 2017-12 /pmc/articles/PMC5726381/ /pubmed/29263778 http://dx.doi.org/10.1111/2041-210X.12810 Text en © 2017 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Evolutionary Biology Wiberg, R. Axel W. Gaggiotti, Oscar E. Morrissey, Michael B. Ritchie, Michael G. Identifying consistent allele frequency differences in studies of stratified populations |
title | Identifying consistent allele frequency differences in studies of stratified populations |
title_full | Identifying consistent allele frequency differences in studies of stratified populations |
title_fullStr | Identifying consistent allele frequency differences in studies of stratified populations |
title_full_unstemmed | Identifying consistent allele frequency differences in studies of stratified populations |
title_short | Identifying consistent allele frequency differences in studies of stratified populations |
title_sort | identifying consistent allele frequency differences in studies of stratified populations |
topic | Evolutionary Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5726381/ https://www.ncbi.nlm.nih.gov/pubmed/29263778 http://dx.doi.org/10.1111/2041-210X.12810 |
work_keys_str_mv | AT wibergraxelw identifyingconsistentallelefrequencydifferencesinstudiesofstratifiedpopulations AT gaggiottioscare identifyingconsistentallelefrequencydifferencesinstudiesofstratifiedpopulations AT morrisseymichaelb identifyingconsistentallelefrequencydifferencesinstudiesofstratifiedpopulations AT ritchiemichaelg identifyingconsistentallelefrequencydifferencesinstudiesofstratifiedpopulations |