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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2511.18948 |
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| _version_ | 1866914168762793984 |
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| author | Bai, Ruilin Chen, Bo |
| author_facet | Bai, Ruilin Chen, Bo |
| contents | X-chromosome association study has specific model uncertainty challenges, such as unknown X-chromosome inactivation status and baseline allele, and considering nonadditive and gene-sex interaction effects in the analysis or not. Although these challenges have been answered for single-locus X-chromosome variants, it remains unclear how to properly perform multilocus association studies when above uncertainties are present. We first carefully investigate the inferential consequences of these uncertainties on existing multilocus association analysis methods, and then propose a theoretically justified framework to analyze multilocus X-chromosome variants while all the uncertainty issues are addressed. We provide separate solutions for common and rare variants, and simulation results show that our solutions are overall more powerful than existing multilocus methods which were proposed to analyze autosomal variants. We finally provide supporting evidences of our approach by revisiting some published X-chromosome association studies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_18948 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | X-chromosome Multilocus Association Studies for Common and Rare Variants Bai, Ruilin Chen, Bo Methodology Applications X-chromosome association study has specific model uncertainty challenges, such as unknown X-chromosome inactivation status and baseline allele, and considering nonadditive and gene-sex interaction effects in the analysis or not. Although these challenges have been answered for single-locus X-chromosome variants, it remains unclear how to properly perform multilocus association studies when above uncertainties are present. We first carefully investigate the inferential consequences of these uncertainties on existing multilocus association analysis methods, and then propose a theoretically justified framework to analyze multilocus X-chromosome variants while all the uncertainty issues are addressed. We provide separate solutions for common and rare variants, and simulation results show that our solutions are overall more powerful than existing multilocus methods which were proposed to analyze autosomal variants. We finally provide supporting evidences of our approach by revisiting some published X-chromosome association studies. |
| title | X-chromosome Multilocus Association Studies for Common and Rare Variants |
| topic | Methodology Applications |
| url | https://arxiv.org/abs/2511.18948 |