ArticleGenetics research2020
A robust test for X-chromosome genetic association accounting for X-chromosome inactivation and imprinting.
Article in Genetics research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 15 citations in OpenAlex.
- The impact of chromosomal sex on cardiometabolic health and disease.Trends in endocrinology and metabolism: TEM · 2023Review
- BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation.BMC bioinformatics · 2022Article
- Gene-Based Methods for Estimating the Degree of the Skewness of X Chromosome Inactivation.Genes · 2022Article
- A statistical measure for the skewness of X chromosome inactivation for quantitative traits and its application to the MCTFR data.BMC genomic data · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The X chromosome is known to play an important role in many sex-specific diseases. However, only a few single-nucleotide polymorphisms on the X chromosome have been found to be associated with diseases. Compared to the autosomes, conducting association tests on the X chromosome is more intractable due to the difference in the number of X chromosomes between females and males. On the other hand, X-chromosome inactivation takes place in female mammals, which is a phenomenon in which the expression of one copy of two X chromosomes in females is silenced in order to achieve the same gene expression level as that in males. In addition, imprinting effects may be related to certain diseases. Currently, there are some existing approaches taking X-chromosome inactivation into account when testing for associations on the X chromosome. However, none of them allows for imprinting effects. Therefore, in this paper, we propose a robust test, ZXCII, which accounts for both X-chromosome inactivation and imprinting effects without requiring specifying the genetic models in advance. Simulation studies are conducted in order to investigate the validity and performance of ZXCII under various scenarios of different parameter values. The simulation results show that ZXCII controls the type I error rate well when there is no association. Furthermore, with regards to power, ZXCII is robust in all of the situations considered and generally outperforms most of the existing methods in the presence of imprinting effects, especially under complete imprinting effects.
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