Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

DNA Microarrays02:34

DNA Microarrays

20.7K
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
20.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Temporal trends in late-pregnancy exposure to ambient temperature and risk of preterm birth in Japan, a nationwide study from 1979 to 2023.

The Lancet regional health. Western Pacific·2026
Same author

Modelling the impacts of meteorological factors on herpangina: a Bayesian spatiotemporal analysis.

Tropical medicine and health·2026
Same author

A comparative simulation study of cluster ensemble algorithms integrated with multiple imputation for clustering with missing data.

BMC medical research methodology·2026
Same author

Establishment of DNA methylation during primate germ cell development.

Nature communications·2026
Same author

Pharmacological interventions for social cognitive impairments in schizophrenia: A systematic review and network meta-analysis of randomized controlled trials.

European psychiatry : the journal of the Association of European Psychiatrists·2026
Same author

Exploring DNA methylation profiles in blood samples of canine gastrointestinal lymphoma.

PloS one·2025

相关实验视频

Updated: Jan 16, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
14:56

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

5.0K

iComBat:在DNA甲基化阵列数据中进行批量效应校正的增量框架.

Yui Tomo1, Ryo Nakaki2

  • 1National Institute of Infectious Diseases, Japan Institute for Health Security, 1-23-1 Toyama, Shinjuku-Ku, 162-0052, Tokyo, Japan.

Computational and structural biotechnology journal
|October 6, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个增量框架来纠正DNA甲基化数据中的批量效应. 这种方法有效地更新了新数据的分析,而不会影响以前处理的样本,这对于纵向衰老研究至关重要.

关键词:
这就是为什么Combat ComBat.经验贝叶斯估计的估计.表观遗传学 在表观遗传学中,表观遗传学是指表观遗传学.一个微阵列的微阵列.重复测量的重复测量

更多相关视频

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
13:47

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

26.2K
A Rat Methyl-Seq Platform to Identify Epigenetic Changes Associated with Stress Exposure
09:06

A Rat Methyl-Seq Platform to Identify Epigenetic Changes Associated with Stress Exposure

Published on: October 24, 2018

11.2K

相关实验视频

Last Updated: Jan 16, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
14:56

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

5.0K
Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
13:47

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

26.2K
A Rat Methyl-Seq Platform to Identify Epigenetic Changes Associated with Stress Exposure
09:06

A Rat Methyl-Seq Platform to Identify Epigenetic Changes Associated with Stress Exposure

Published on: October 24, 2018

11.2K

科学领域:

  • 表观遗传学 在表观遗传学中,表观遗传学是指表观遗传学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • DNA甲基化模式对于理解疾病和衰老至关重要.
  • 在DNA甲基化阵列数据分析中的批量效应可以掩盖生物信号.
  • 当前的批量校正方法需要在添加新样本时重新分析所有数据.

研究的目的:

  • 在DNA甲基化数据中开发一个批量效应校正的增量框架.
  • 根据新数据的可用性,使分析能够有效地更新.
  • 以重复DNA甲基化测量为纵向研究的支持.

主要方法:

  • 开发了一个增量批次校正框架.
  • 该框架基于ComBat,使用贝叶斯层次模型和经验贝叶斯估计.
  • 该方法调整位置和尺度参数以进行批量效应校正.

主要成果:

  • 提出的方法成功地在新添加的数据中纠正了批量效应.
  • 纠正新数据并不需要重新纠正先前分析的数据.
  • 数字实验和现实世界的数据验证了该方法的有效性.

结论:

  • 增量框架为纵向DNA甲基化研究中的批量效应校正提供了有效的解决方案.
  • 这种方法对于涉及抗衰老干预和重复测量的临床试验尤为有价值.
  • 方便对随着时间的推移而发生的动态表观遗传变化进行可靠的分析.