ArticleGenetic epidemiology2014
X-chromosome genetic association test accounting for X-inactivation, skewed X-inactivation, and escape from X-inactivation.
Article in Genetic epidemiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 4 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- X chromosome associations with chronic obstructive pulmonary disease and related phenotypes: an X chromosome-wide association study.Respiratory research · 2023Pooled it
- A systematic review of analytical methods used in genetic association analysis of the X-chromosome.Briefings in bioinformatics · 2022Pooled it
- No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis.Scientific reports · 2016Pooled it
- Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder.Human molecular genetics · 2016Pooled it
- X chromosome-wide association studies for quantitative trait loci based on the mixture of general pedigrees and additional unrelated individuals.Briefings in bioinformatics · 2026Article
- X chromosome inactivation across primary human tissues is mostly complete, with significant implications for genetic and clinical studies.BMC genomics · 2025Article
- Eight quick tips for including chromosome X in genome-wide association studies.PLoS computational biology · 2024Article
- Leveraging sex-genetic interactions to understand brain disorders: recent advances and current gaps.Brain communications · 2024Review
- eXclusionarY: 10 years later, where are the sex chromosomes in GWASs?American journal of human genetics · 2023Review
- An Efficient Bayesian Method for Estimating the Degree of the Skewness of X Chromosome Inactivation Based on the Mixture of General Pedigrees and Unrelated Females.Biomolecules · 2023Article
- X chromosome-wide association study of quantitative biomarkers from the Alzheimer's Disease Neuroimaging Initiative study.Frontiers in aging neuroscience · 2023Article
- Article
- BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation.BMC bioinformatics · 2022Article
- Article
- Gene-Based Methods for Estimating the Degree of the Skewness of X Chromosome Inactivation.Genes · 2022Article
- Major sex differences in allele frequencies for X chromosomal variants in both the 1000 Genomes Project and gnomAD.PLoS genetics · 2022Article
- Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy.Journal of personalized medicine · 2022Review
- Comparison of Methods Utilizing Sex-Specific PRSs Derived From GWAS Summary Statistics.Frontiers in genetics · 2022Article
- Association Study ofFrontiers in neuroscience · 2022Article
- The X factor: A robust and powerful approach to X-chromosome-inclusive whole-genome association studies.Genetic epidemiology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
X-chromosome inactivation (XCI) is the process in which one of the two copies of the X-chromosome in females is randomly inactivated to achieve the dosage compensation of X-linked genes between males and females. That is, 50% of the cells have one allele inactive and the other 50% of the cells have the other allele inactive. However, studies have shown that skewed or nonrandom XCI is a biological plausibility wherein more than 75% of cells have the same allele inactive. Also, some of the X-chromosome genes escape XCI, i.e., both alleles are active in all cells. Current statistical tests for X-chromosome association studies can either account for random XCI (e.g., Clayton's approach) or escape from XCI (e.g., PLINK software). Because the true XCI process is unknown and differs across different regions on the X-chromosome, we proposed a unified approach of maximizing likelihood ratio over all biological possibilities: random XCI, skewed XCI, and escape from XCI. A permutation-based procedure was developed to assess the significance of the approach. We conducted simulation studies to compare the performance of the proposed approach with Clayton's approach and PLINK regression. The results showed that the proposed approach has higher powers in the scenarios where XCI is skewed while losing some power in scenarios where XCI is random or XCI is escaped, with well-controlled type I errors. We also applied the approach to the X-chromosomal genetic association study of head and neck cancer.
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