St Andrews Research Repository

St Andrews University Home
View Item 
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  • Register / Login
JavaScript is disabled for your browser. Some features of this site may not work without it.

A note on simulating null distributions for G matrix comparisons

Thumbnail
View/Open
Morrissey_2019_Evolution_Gmatrix_AAM.pdf (365.1Kb)
Date
22/10/2019
Author
Morrissey, Michael B.
Hangartner, Sandra
Monro, Keyne
Funder
The Royal Society
Grant ID
UF130398
Keywords
Differentiation
G matrix
Null distribution
Quantitiatve genetics
Tensor analysis
QA Mathematics
QH301 Biology
3rd-DAS
Metadata
Show full item record
Abstract
Genetic variances and covariances, summarised in G matrices, are key determinants of the course of adaptive evolution. Consequently, understanding how G matrices vary among populations is critical to answering a variety of questions in evolutionary biology. A method has recently been proposed for generating null distributions of statistics pertaining to differences in G matrices among populations. The general approach facilitated by this method is likely to prove to be very important in studies of the evolution of G . We have identified an issue in the method that will cause it to create null distributions of differences in G matrices that are likely to be far too narrow. The issue arises from the fact that the method as currently used generates null distributions of statistics pertaining to differences in G matrices across populations by simulating breeding value vectors based on G matrices estimated from data, randomising these vectors across populations, and then calculating null values of statistics from G matrices that are calculated directly from the variances and covariances among randomised vectors. This calculation treats breeding values as quantities that are directly measurable, instead of predicted from G matrices that are themselves estimated from patterns of covariance among kin. The existing method thus neglects a major source of uncertainty in G matrices, which renders it anticonservative. We first suggest a correction to the method. We then apply the original and modified methods to a very simple instructive scenario. Finally, we demonstrate the use of both methods in the analysis of a real data set.
Citation
Morrissey , M B , Hangartner , S & Monro , K 2019 , ' A note on simulating null distributions for G matrix comparisons ' , Evolution , vol. Early View . https://doi.org/10.1111/evo.13842
Publication
Evolution
Status
Peer reviewed
DOI
https://doi.org/10.1111/evo.13842
ISSN
0014-3820
Type
Journal article
Rights
© 2019 The Author(s). Evolution © 2019 The Society for the Study of Evolution. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1111/evo.13842
Description
MBM is supported by a University Research Fellowship from the Royal Society (London). KM is supported by a Future Fellowship from the Australian Research Council.
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/20809

Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

Advanced Search

Browse

All of RepositoryCommunities & CollectionsBy Issue DateNamesTitlesSubjectsClassificationTypeFunderThis CollectionBy Issue DateNamesTitlesSubjectsClassificationTypeFunder

My Account

Login

Open Access

To find out how you can benefit from open access to research, see our library web pages and Open Access blog. For open access help contact: openaccess@st-andrews.ac.uk.

Accessibility

Read our Accessibility statement.

How to submit research papers

The full text of research papers can be submitted to the repository via Pure, the University's research information system. For help see our guide: How to deposit in Pure.

Electronic thesis deposit

Help with deposit.

Repository help

For repository help contact: Digital-Repository@st-andrews.ac.uk.

Give Feedback

Cookie policy

This site may use cookies. Please see Terms and Conditions.

Usage statistics

COUNTER-compliant statistics on downloads from the repository are available from the IRUS-UK Service. Contact us for information.

© University of St Andrews Library

University of St Andrews is a charity registered in Scotland, No SC013532.

  • Facebook
  • Twitter