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

Genomics02:02

Genomics

37.5K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
37.5K
Causality in Epidemiology01:21

Causality in Epidemiology

912
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
912
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

163
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
163
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

14.4K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
14.4K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

705
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
705
Multiple Allele Traits01:49

Multiple Allele Traits

35.0K
The Concept of Multiple Allelism
35.0K

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

Plasma GDF15 affects long-term dementia risk and alters neuroimmune signaling.

Science advances·2026
Same author

EBV strain interacts with host HLA to drive nasopharyngeal carcinoma risk.

Nature·2026
Same author

Mendelian Randomization Methods for Causal Inference: Estimands, Identification and Inference.

Statistics in medicine·2026
Same author

CoxMDS: multiple data splitting for high-dimensional mediation analysis with survival outcomes in epigenome-wide studies.

Briefings in bioinformatics·2026
Same author

Boosting the Power of Rare Variant Association Studies by Imputation Using Large-scale Sequencing Population.

Genomics, proteomics & bioinformatics·2025
Same author

Shared genetic link and causal inference between blood lipids, lipid-lowering drugs and amyotrophic lateral sclerosis.

Neural regeneration research·2025

相关实验视频

Updated: Sep 18, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.5K

一个介绍多omics数据的因果推理方法.

Minhao Yao1, Zhonghua Liu2

  • 1Department of Statistics and Actuarial Science, University of Hong Kong, Hong Kong SAR, China.

Current protocols
|June 25, 2025
PubMed
概括
此摘要是机器生成的。

这项研究探讨了孟德尔随机化 (MR) 用于识别个人化医学中的奥米克生物标志物. 它详细介绍了挑战,并介绍了四种R可执行的MR方法,用于分析多omics数据,如表观遗传学和蛋白质学.

关键词:
门德尔的随机化有关因果推理的推理.这是一个仪器变量.调解分析 调解分析多个学科的数据数据.

更多相关视频

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.2K

相关实验视频

Last Updated: Sep 18, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.5K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.2K

科学领域:

  • 遗传学和生物信息学 遗传学和生物信息学
  • 个性化医疗是个性化的医疗.
  • 因果推理因果推理

背景情况:

  • 欧米克生物标志物对个性化医学至关重要,为疾病病因学,诊断和治疗提供了分子洞察力.
  • 奥米克技术的进步产生了大量的多式联络数据,使人类疾病的新生物标志物发现成为可能.
  • 门德尔随机化 (MR) 是一种因果推理方法,使用遗传变异作为工具变量来解决混偏差.

研究的目的:

  • 用omics数据进行MR分析所面临的挑战.
  • 介绍和描述四种用于分析多omics数据的MR方法.
  • 为表观遗传学,转录遗传学,蛋白质遗传学和代谢遗传学数据分析提供R可执行的方法.

主要方法:

  • 审查当前在将MR应用于omics数据方面的挑战.
  • 描述了四种不同的MR方法,适用于多个OMIC数据集.
  • 在R统计软件环境中对这些方法的实施指南.

主要成果:

  • 确定omics数据驱动型MR的主要挑战.
  • 对四种MR方法的详细解释,适用于各种omics数据类型.
  • 演示基于R的执行,用于实际应用.

结论:

  • 提出的MR方法提供了一个强大的框架,用于用多omics数据进行因果推理.
  • 这些R-executable工具有助于识别疾病病因和向治疗的omics生物标志物.
  • 这项工作促进了因果推理在个性化医学中的应用,使用综合的奥米克学方法.