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BEXCIS:用于估计 X 染色体失活程度偏度的贝叶斯方法。

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

机构信息

Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.

Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China.

出版信息

BMC Bioinformatics. 2022 May 24;23(1):193. doi: 10.1186/s12859-022-04721-y.

Abstract

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 .

摘要

背景

X 染色体失活(XCI)是一种表观遗传现象,即女性的两条 X 染色体中的一条在胚胎早期发育过程中被转录沉默。偏倚的 XCI 与一些 X 连锁疾病有关。已经有几种方法可以测量 XCI 偏倚的程度。然而,这些方法可能仍然存在一些局限性。

结果

我们提出了一种贝叶斯方法,通过纳入其在 0 和 2 之间的先验信息,来获得 XCI 偏倚程度的点估计和置信区间。我们考虑了正态先验和均匀先验(分别表示为 BN 和 BU)。我们还提出了一种基于惩罚费勒法的惩罚点估计,并推导出相应的置信区间。模拟结果表明,BN 和 BU 方法可以解决极端点估计、非信息区间、空集和不连续区间的问题。BN 方法通常优于其他方法,在点估计中具有最低的均方误差,在区间估计中具有最小的中位数和区间宽度变化,从而很好地控制了覆盖率概率。我们将所有方法应用于 Graves 病数据和明尼苏达州双胞胎和家庭研究中心的数据,并发现 Graves 病数据中的 SNP rs3827440 可能会发生向等位基因 C 偏倚的 XCI。

结论

我们建议在实践中使用 BN 方法来测量 XCI 偏倚的程度。R 包 BEXCIS 可在 https://github.com/Wen-YiYu/BEXCIS 上公开获取。

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