MammalMethylClock R 软件包：哺乳动物基于 DNA 甲基化的表观遗传时钟软件。

IF 4.4 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2024-04-24 DOI:10.1093/bioinformatics/btae280

J. Zoller, Steve Horvath

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引用次数: 0

摘要

动机表观遗传时钟是一种基于特定物种或物种集 DNA 甲基化水平的预测方法。这些基于 DNA 甲基化的年龄或死亡风险生物标志物被定义为多变量回归模型，在物种保护工作和临床前研究中非常有用。结果我们提出了一个名为 MammalMethylClock 的 R 软件包，用于构建、评估和应用不同哺乳动物物种的表观遗传时钟。该 R 软件包包括用于实现哺乳动物甲基化联盟（Mammalian Methylation Consortium）已有哺乳动物时钟的实用程序。可获得性MammalMethylClock 的源代码和文档手册以及该软件包中包含的时钟系数 .csv 文件可在 Zenodo 上找到，网址是：https://doi.org/10.5281/zenodo.10971037.SUPPLEMENTARY 信息补充数据可在 Bioinformatics online 上获得。

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MammalMethylClock R package: Software for DNA Methylation-Based epigenetic clocks in mammals.

MOTIVATION Epigenetic clocks are prediction methods based on DNA methylation levels in a given species or set of species. Defined as multivariate regression models, these DNA methylation-based biomarkers of age or mortality risk are useful in species conservation efforts and in preclinical studies. RESULTS We present an R package called MammalMethylClock for the construction, assessment, and application of epigenetic clocks in different mammalian species. The R package includes the utility for implementing pre-existing mammalian clocks from the Mammalian Methylation Consortium. AVAILABILITY The source code and documentation manual for MammalMethylClock, and clock coefficient .csv files that are included within this software package, can be found on Zenodo at https://doi.org/10.5281/zenodo.10971037. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

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来源期刊

Bioinformatics 生物-生化研究方法

CiteScore

11.20

自引率

5.20%

发文量

753

审稿时长

2.1 months

期刊介绍： The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.