Accessibility navigation


pKWmEB: integration of Kruskal-Wallis test with empirical bayes under polygenic background control for multi-locus genome-wide association study

Ren, W.-L., Wen, Y.-J., Dunwell, J. and Zhang, Y.-M. (2018) pKWmEB: integration of Kruskal-Wallis test with empirical bayes under polygenic background control for multi-locus genome-wide association study. Heredity, 120. pp. 208-218. ISSN 1365-2540

[img]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

1MB
[img]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.

691kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1038/s41437-017-0007-4

Abstract/Summary

Although nonparametric methods in genome-wide association studies (GWAS) are robust in quantitative trait nucleotide (QTN) detection, the absence of polygenic background control in single-marker association in genome-wide scans results in a high false positive rate. To overcome this issue, we proposed an integrated nonparametric method for multi-locus GWAS. First, a new model transformation was used to whiten the covariance matrix of polygenic matrix K and environmental noise. Using the transferred model, Kruskal–Wallis test along with least angle regression was then used to select all the markers that were potentially associated with the trait. Finally, all the selected markers were placed into multi-locus model, these effects were estimated by empirical Bayes, and all the nonzero effects were further identified by a likelihood ratio test for true QTN detection. This method, named pKWmEB, was validated by a series of Monte Carlo simulation studies. As a result, pKWmEB effectively controlled false positive rate, although a less stringent significance criterion was adopted. More importantly, pKWmEB retained the high power of Kruskal–Wallis test, and provided QTN effect estimates. To further validate pKWmEB, we re-analyzed four flowering time related traits in Arabidopsis thaliana, and detected some previously reported genes that were not identified by the other methods.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Centre for Food Security
Faculty of Life Sciences > School of Agriculture, Policy and Development > Biodiversity, Crops and Agroecosystems Division > Crops Research Group
ID Code:72952
Publisher:Nature Publishing Group

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation