Genomic imprinting is an epigenetic mechanism that leads to differential contributions of maternal and paternal alleles to offspring gene expression in a parent-of-origin manner. We propose a novel test for detecting the parent-of-origin effects (POEs) in genome wide genotype data from related individuals (twins) when the parental origin cannot be inferred. The proposed method exploits a finite mixture of linear mixed models: the key idea is that in the case of POEs the population can be clustered in two different groups in which the reference allele is inherited by a different parent. A further advantage of this approach is the possibility to obtain an estimation of parental effect when the parental information is missing. We will also show that the approach is flexible enough to be applicable to the general scenario of independent data. The performance of the proposed test is evaluated through a wide simulation study. The method is finally applied to known imprinted genes of the MuTHER twin study data.

Chiara Sacco, Cinzia Viroli, Mario Falchi (2017). A statistical test for detecting parent-of-origin effects when parental information is missing. STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY, 16(4), 275-289 [10.1515/sagmb-2017-0007].

A statistical test for detecting parent-of-origin effects when parental information is missing

SACCO, CHIARA;VIROLI, CINZIA;
2017

Abstract

Genomic imprinting is an epigenetic mechanism that leads to differential contributions of maternal and paternal alleles to offspring gene expression in a parent-of-origin manner. We propose a novel test for detecting the parent-of-origin effects (POEs) in genome wide genotype data from related individuals (twins) when the parental origin cannot be inferred. The proposed method exploits a finite mixture of linear mixed models: the key idea is that in the case of POEs the population can be clustered in two different groups in which the reference allele is inherited by a different parent. A further advantage of this approach is the possibility to obtain an estimation of parental effect when the parental information is missing. We will also show that the approach is flexible enough to be applicable to the general scenario of independent data. The performance of the proposed test is evaluated through a wide simulation study. The method is finally applied to known imprinted genes of the MuTHER twin study data.
2017
Chiara Sacco, Cinzia Viroli, Mario Falchi (2017). A statistical test for detecting parent-of-origin effects when parental information is missing. STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY, 16(4), 275-289 [10.1515/sagmb-2017-0007].
Chiara Sacco; Cinzia Viroli; Mario Falchi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/608383
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