Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1469-1809.2006.00268.x
Title: Extreme rank selections for linkage analysis of quantitative trait loci using selected sib-pairs
Authors: Zheng, G.
Ghosh, K.
Chen, Z. 
Li, Z.
Keywords: Extreme rank selection (ERS)
Linkage
QTL
Ranked set sampling (RSS)
Truncationselection (TS)
Issue Date: Nov-2006
Citation: Zheng, G., Ghosh, K., Chen, Z., Li, Z. (2006-11). Extreme rank selections for linkage analysis of quantitative trait loci using selected sib-pairs. Annals of Human Genetics 70 (6) : 857-866. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1469-1809.2006.00268.x
Abstract: It is well known that linkage analysis using simple random sib-pairs has relatively low power for detecting quantitative trait loci with small genetic effects. The power can be substantially increased by using samples selected based on their trait values. Usually, samples that are obtained by truncation selection consist of random samples from a truncated trait distribution. In this article we propose an alternative method using extreme ranks for linkage analysis with selected sib-pairs. This approach approximates the truncation selection. With similar screening sizes and the same sample size of selected sib-pairs, the extreme rank selection and truncation method have similar power performance, both of which are substantially more powerful than when using random sib-pairs. Simulation results on the comparison of powers between the truncation selection and the extreme rank selection and/or random selection for linkage analysis are reported. © 2006 University College London.
Source Title: Annals of Human Genetics
URI: http://scholarbank.nus.edu.sg/handle/10635/105149
ISSN: 00034800
DOI: 10.1111/j.1469-1809.2006.00268.x
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

4
checked on Sep 19, 2018

WEB OF SCIENCETM
Citations

3
checked on Sep 10, 2018

Page view(s)

35
checked on Jul 27, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.