ArticleHuman heredity2011
Association tests for X-chromosomal markers--a comparison of different test statistics.
Article in Human heredity, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 4 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Assessment of the functionality and usability of open-source rare variant analysis pipelines.Briefings in bioinformatics · 2025Pooled it
- A systematic review of analytical methods used in genetic association analysis of the X-chromosome.Briefings in bioinformatics · 2022Pooled it
- A genome-wide association study implicates the BMP7 locus as a risk factor for nonsyndromic metopic craniosynostosis.Human genetics · 2020Pooled it
- No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis.Scientific reports · 2016Pooled it
- X chromosome inactivation across primary human tissues is mostly complete, with significant implications for genetic and clinical studies.BMC genomics · 2025Article
- Methodological opportunities in genomic data analysis to advance health equity.Nature reviews. Genetics · 2025Review
- Childhood Juvenile idiopathic arthritis combined with Klinefelter syndrome: a case report and literature review.American journal of translational research · 2025Article
- Review
- Article
- Major sex differences in allele frequencies for X chromosomal variants in both the 1000 Genomes Project and gnomAD.PLoS genetics · 2022Article
- The X factor: A robust and powerful approach to X-chromosome-inclusive whole-genome association studies.Genetic epidemiology · 2021Article
- Testing and estimation of X-chromosome SNP effects: Impact of model assumptions.Genetic epidemiology · 2021Article
- A robust test for X-chromosome genetic association accounting for X-chromosome inactivation and imprinting.Genetics research · 2020Article
- X chromosome genetic data in a Spanish children cohort, dataset description and analysis pipeline.Scientific data · 2019Article
- The role of sex in the genomics of human complex traits.Nature reviews. Genetics · 2019Review
- Selection of X-chromosome Inactivation Model.Cancer informatics · 2017Article
- Modeling X Chromosome Data Using Random Forests: Conquering Sex Bias.Genetic epidemiology · 2016Article
- Evaluating the Calibration and Power of Three Gene-Based Association Tests of Rare Variants for the X Chromosome.Genetic epidemiology · 2015Article
- X-inactivation informs variance-based testing for X-linked association of a quantitative trait.BMC genomics · 2015Article
- Influence of Feature Encoding and Choice of Classifier on Disease Risk Prediction in Genome-Wide Association Studies.PloS one · 2015Article
Corrections and comments
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveGenome-wide association studies have successfully elucidated the genetic background of complex diseases, but X chromosomal data have usually not been analyzed. A reason for this is that there is no consensus approach for the analysis taking into account the specific features of X chromosomal data. This contribution evaluates test statistics proposed for X chromosomal markers regarding type I error frequencies and power.
methodsWe performed extensive simulation studies covering a wide range of different settings. Besides characteristics of the general population, we investigated sex-balanced or unbalanced sampling procedures as well as sex-specific effect sizes, allele frequencies and prevalence. Finally, we applied the test statistics to an association data set on Crohn's disease.
resultsSimulation results imply that in addition to standard quality control, sex-specific allele frequencies should be checked to control for type I errors. Furthermore, we observed distinct differences in power between test statistics which are determined by sampling design and sex specificity of effect sizes. Analysis of the Crohn's disease data detects two previously unknown genetic regions on the X chromosome.
conclusionAlthough no test is uniformly most powerful under all settings, recommendations are offered as to which test performs best under certain conditions.
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