Abstract：
:We present theoretical explanations and show through simulation that the individual admixture proportion estimates obtained by using ancestry informative markers should be seen as an error-contaminated measurement of the underlying individual ancestry proportion. These estimates can be used in structured association tests as a control variable to limit type I error inflation or reduce loss of power due to population stratification observed in studies of admixed populations. However, the inclusion of such error-containing variables as covariates in regression models can bias parameter estimates and reduce ability to control for the confounding effect of admixture in genetic association tests. Measurement error correction methods offer a way to overcome this problem but require an a priori estimate of the measurement error variance. We show how an upper bound of this variance can be obtained, present four measurement error correction methods that are applicable to this problem, and conduct a simulation study to compare their utility in the case where the admixed population results from the intermating between two ancestral populations. Our results show that the quadratic measurement error correction (QMEC) method performs better than the other methods and maintains the type I error to its nominal level.
journal_name
Geneticsjournal_title
Geneticsauthors
Divers J,Vaughan LK,Padilla MA,Fernandez JR,Allison DB,Redden DTdoi
10.1534/genetics.107.075408subject
Has Abstractpub_date
2007-07-01 00:00:00pages
1823-33issue
3eissn
0016-6731issn
1943-2631pii
genetics.107.075408journal_volume
176pub_type
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