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Article: A statistical measure for the skewness of X chromosome inactivation based on case-control design
Title | A statistical measure for the skewness of X chromosome inactivation based on case-control design |
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Authors | |
Keywords | Case-control design Confidence interval Graves' disease Skewness X chromosome inactivation |
Issue Date | 2019 |
Publisher | BioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcbioinformatics/ |
Citation | BMC Bioinformatics, 2019, v. 20, p. article no. 11:1-11 How to Cite? |
Abstract | Background: Skewed X chromosome inactivation (XCI), which is a non-random process, is frequently observed in both healthy and affected females. Furthermore, skewed XCI has been reported to be related to many X-linked diseases. However, no statistical method is available in the literature to measure the degree of the skewness of XCI for case-control design. Therefore, it is necessary to develop methods for such a task. Results: In this article, we first proposed a statistical measure for the degree of XCI skewing by using a case-control design, which is a ratio of two logistic regression coefficients after a simple reparameterization. Based on the point estimate of the ratio, we further developed three types of confidence intervals (the likelihood ratio, Fieller's and delta methods) to evaluate its variation. Simulation results demonstrated that the likelihood ratio method and the Fieller's method have more accurate coverage probability and more balanced tail errors than the delta method. We also applied these proposed methods to analyze the Graves' disease data for their practical use and found that rs3827440 probably undergoes a skewed XCI pattern with 68.7% of cells in heterozygous females having the risk allele T active, while the other 31.3% of cells keeping the normal allele C active. Conclusions: For practical application, we suggest using the Fieller's method in large samples due to the non-iterative computation procedure and using the LR method otherwise for its robustness despite its slightly heavy computational burden. © 2019 The Author(s). |
Persistent Identifier | http://hdl.handle.net/10722/272975 |
ISSN | 2023 Impact Factor: 2.9 2023 SCImago Journal Rankings: 1.005 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wang, P | - |
dc.contributor.author | Zhang, Y | - |
dc.contributor.author | Wang, BQ | - |
dc.contributor.author | Li, JL | - |
dc.contributor.author | Wang, YX | - |
dc.contributor.author | Pan, D | - |
dc.contributor.author | Wu, XB | - |
dc.contributor.author | Fung, WK | - |
dc.contributor.author | Zhou, JY | - |
dc.date.accessioned | 2019-08-06T09:20:13Z | - |
dc.date.available | 2019-08-06T09:20:13Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | BMC Bioinformatics, 2019, v. 20, p. article no. 11:1-11 | - |
dc.identifier.issn | 1471-2105 | - |
dc.identifier.uri | http://hdl.handle.net/10722/272975 | - |
dc.description.abstract | Background: Skewed X chromosome inactivation (XCI), which is a non-random process, is frequently observed in both healthy and affected females. Furthermore, skewed XCI has been reported to be related to many X-linked diseases. However, no statistical method is available in the literature to measure the degree of the skewness of XCI for case-control design. Therefore, it is necessary to develop methods for such a task. Results: In this article, we first proposed a statistical measure for the degree of XCI skewing by using a case-control design, which is a ratio of two logistic regression coefficients after a simple reparameterization. Based on the point estimate of the ratio, we further developed three types of confidence intervals (the likelihood ratio, Fieller's and delta methods) to evaluate its variation. Simulation results demonstrated that the likelihood ratio method and the Fieller's method have more accurate coverage probability and more balanced tail errors than the delta method. We also applied these proposed methods to analyze the Graves' disease data for their practical use and found that rs3827440 probably undergoes a skewed XCI pattern with 68.7% of cells in heterozygous females having the risk allele T active, while the other 31.3% of cells keeping the normal allele C active. Conclusions: For practical application, we suggest using the Fieller's method in large samples due to the non-iterative computation procedure and using the LR method otherwise for its robustness despite its slightly heavy computational burden. © 2019 The Author(s). | - |
dc.language | eng | - |
dc.publisher | BioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcbioinformatics/ | - |
dc.relation.ispartof | BMC Bioinformatics | - |
dc.rights | BMC Bioinformatics. Copyright © BioMed Central Ltd. | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Case-control design | - |
dc.subject | Confidence interval | - |
dc.subject | Graves' disease | - |
dc.subject | Skewness | - |
dc.subject | X chromosome inactivation | - |
dc.title | A statistical measure for the skewness of X chromosome inactivation based on case-control design | - |
dc.type | Article | - |
dc.identifier.email | Fung, WK: wingfung@hkucc.hku.hk | - |
dc.identifier.authority | Fung, WK=rp00696 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1186/s12859-018-2587-2 | - |
dc.identifier.pmid | 30616589 | - |
dc.identifier.pmcid | PMC6323862 | - |
dc.identifier.scopus | eid_2-s2.0-85059589513 | - |
dc.identifier.hkuros | 300031 | - |
dc.identifier.volume | 20 | - |
dc.identifier.issue | 11 | - |
dc.identifier.spage | article no. 11:1 | - |
dc.identifier.epage | 11 | - |
dc.identifier.isi | WOS:000455093300003 | - |
dc.publisher.place | United Kingdom | - |
dc.identifier.issnl | 1471-2105 | - |