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BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation

BACKGROUND: X chromosome inactivation (XCI) is an epigenetic phenomenon that one of two X chromosomes in females is transcriptionally silenced during early embryonic development. Skewed XCI has been reported to be associated with some X-linked diseases. There have been several methods measuring the...

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Autores principales: Yu, Wen-Yi, Zhang, Yu, Li, Meng-Kai, Yang, Zi-Ying, Fung, Wing Kam, Zhao, Pei-Zhen, Zhou, Ji-Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9128296/
https://www.ncbi.nlm.nih.gov/pubmed/35610583
http://dx.doi.org/10.1186/s12859-022-04721-y
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author Yu, Wen-Yi
Zhang, Yu
Li, Meng-Kai
Yang, Zi-Ying
Fung, Wing Kam
Zhao, Pei-Zhen
Zhou, Ji-Yuan
author_facet Yu, Wen-Yi
Zhang, Yu
Li, Meng-Kai
Yang, Zi-Ying
Fung, Wing Kam
Zhao, Pei-Zhen
Zhou, Ji-Yuan
author_sort Yu, Wen-Yi
collection PubMed
description BACKGROUND: X chromosome inactivation (XCI) is an epigenetic phenomenon that one of two X chromosomes in females is transcriptionally silenced during early embryonic development. Skewed XCI has been reported to be associated with some X-linked diseases. There have been several methods measuring the degree of the skewness of XCI. However, these methods may still have several limitations. RESULTS: We propose a Bayesian method to obtain the point estimate and the credible interval of the degree of XCI skewing by incorporating its prior information of being between 0 and 2. We consider a normal prior and a uniform prior for it (respectively denoted by BN and BU). We also propose a penalized point estimate based on the penalized Fieller’s method and derive the corresponding confidence interval. Simulation results demonstrate that the BN and BU methods can solve the problems of extreme point estimates, noninformative intervals, empty sets and discontinuous intervals. The BN method generally outperforms other methods with the lowest mean squared error in the point estimation, and well controls the coverage probability with the smallest median and the least variation of the interval width in the interval estimation. We apply all the methods to the Graves’ disease data and the Minnesota Center for Twin and Family Research data, and find that SNP rs3827440 in the Graves’ disease data may undergo skewed XCI towards the allele C. CONCLUSIONS: We recommend the BN method for measuring the degree of the skewness of XCI in practice. The R package BEXCIS is publicly available at https://github.com/Wen-YiYu/BEXCIS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04721-y.
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spelling pubmed-91282962022-05-25 BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation Yu, Wen-Yi Zhang, Yu Li, Meng-Kai Yang, Zi-Ying Fung, Wing Kam Zhao, Pei-Zhen Zhou, Ji-Yuan BMC Bioinformatics Research BACKGROUND: X chromosome inactivation (XCI) is an epigenetic phenomenon that one of two X chromosomes in females is transcriptionally silenced during early embryonic development. Skewed XCI has been reported to be associated with some X-linked diseases. There have been several methods measuring the degree of the skewness of XCI. However, these methods may still have several limitations. RESULTS: We propose a Bayesian method to obtain the point estimate and the credible interval of the degree of XCI skewing by incorporating its prior information of being between 0 and 2. We consider a normal prior and a uniform prior for it (respectively denoted by BN and BU). We also propose a penalized point estimate based on the penalized Fieller’s method and derive the corresponding confidence interval. Simulation results demonstrate that the BN and BU methods can solve the problems of extreme point estimates, noninformative intervals, empty sets and discontinuous intervals. The BN method generally outperforms other methods with the lowest mean squared error in the point estimation, and well controls the coverage probability with the smallest median and the least variation of the interval width in the interval estimation. We apply all the methods to the Graves’ disease data and the Minnesota Center for Twin and Family Research data, and find that SNP rs3827440 in the Graves’ disease data may undergo skewed XCI towards the allele C. CONCLUSIONS: We recommend the BN method for measuring the degree of the skewness of XCI in practice. The R package BEXCIS is publicly available at https://github.com/Wen-YiYu/BEXCIS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04721-y. BioMed Central 2022-05-24 /pmc/articles/PMC9128296/ /pubmed/35610583 http://dx.doi.org/10.1186/s12859-022-04721-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yu, Wen-Yi
Zhang, Yu
Li, Meng-Kai
Yang, Zi-Ying
Fung, Wing Kam
Zhao, Pei-Zhen
Zhou, Ji-Yuan
BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation
title BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation
title_full BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation
title_fullStr BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation
title_full_unstemmed BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation
title_short BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation
title_sort bexcis: bayesian methods for estimating the degree of the skewness of x chromosome inactivation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9128296/
https://www.ncbi.nlm.nih.gov/pubmed/35610583
http://dx.doi.org/10.1186/s12859-022-04721-y
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