dc.contributor.author |
McMillan, Louise |
en |
dc.contributor.author |
Fewster, Rachel |
en |
dc.date.accessioned |
2018-11-04T21:04:23Z |
en |
dc.date.issued |
2017-09 |
en |
dc.identifier.citation |
Biometrics 73(3):1029-1041 Sep 2017 |
en |
dc.identifier.issn |
0006-341X |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/43810 |
en |
dc.description.abstract |
We propose a method for visualizing genetic assignment data by characterizing the distribution of genetic profiles for each candidate source population. This method enhances the assignment method of Rannala and Mountain (1997) by calculating appropriate graph positions for individuals for which some genetic data are missing. An individual with missing data is positioned in the distributions of genetic profiles for a population according to its estimated quantile based on its available data. The quantiles of the genetic profile distribution for each population are calculated by approximating the cumulative distribution function (CDF) using the saddlepoint method, and then inverting the CDF to get the quantile function. The saddlepoint method also provides a way to visualize assignment results calculated using the leave-one-out procedure. This new method offers an advance upon assignment software such as geneclass2, which provides no visualization method, and is biologically more interpretable than the bar charts provided by the software structure. We show results from simulated data and apply the methods to microsatellite genotype data from ship rats (Rattus rattus) captured on the Great Barrier Island archipelago, New Zealand. The visualization method makes it straightforward to detect features of population structure and to judge the discriminative power of the genetic data for assigning individuals to source populations. |
en |
dc.publisher |
Wiley |
en |
dc.relation.ispartofseries |
Biometrics |
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dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights |
This is the peer reviewed version of the article, which has been published in final form at http://dx.doi.org/10.1111/biom.12667. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.rights.uri |
http://www.biometrics.tibs.org/guidelinesforposting.htm |
en |
dc.title |
Visualizations for genetic assignment analyses using the saddlepoint approximation method |
en |
dc.type |
Journal Article |
en |
dc.identifier.doi |
10.1111/biom.12667 |
en |
pubs.issue |
3 |
en |
pubs.begin-page |
1029 |
en |
pubs.volume |
73 |
en |
dc.rights.holder |
Copyright: The International Biometric Society |
en |
dc.identifier.pmid |
28182851 |
en |
pubs.author-url |
http://onlinelibrary.wiley.com/doi/10.1111/biom.12667/full |
en |
pubs.end-page |
1041 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
Article |
en |
pubs.elements-id |
612496 |
en |
pubs.org-id |
Science |
en |
pubs.org-id |
Statistics |
en |
pubs.record-created-at-source-date |
2017-02-13 |
en |
pubs.online-publication-date |
2017-02-09 |
en |
pubs.dimensions-id |
28182851 |
en |