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相关概念视频

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

13.3K
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...
13.3K
Genetic Screens02:46

Genetic Screens

4.9K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
4.9K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

17.7K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
17.7K
Wilcoxon Signed-Ranks Test for Median of Single Population01:14

Wilcoxon Signed-Ranks Test for Median of Single Population

114
The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
114
Epistasis Analysis01:09

Epistasis Analysis

4.9K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
4.9K
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

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Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
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相关实验视频

Updated: Jun 19, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

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基准比较 门德尔随机化方法用于使用全基因组关联研究总结统计的因果推断.

Xianghong Hu1, Mingxuan Cai2, Jiashun Xiao3

  • 1School of Mathematical Sciences, Institute of Statistical Sciences, Shenzhen University, Shenzhen 518060, China; Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China.

American journal of human genetics
|July 26, 2024
PubMed
概括

这项研究使用现实世界遗传数据对16种门德尔随机化 (MR) 方法进行了基准测试. 它评估了它们在混下的可靠性,准确性和功率,为因果推理研究提供了实际指导方针.

关键词:
关于GWAS总结统计数据的总结门德尔的随机化有关因果推理的推理.造成混的因素.负控制是一种消极的控制.

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

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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相关实验视频

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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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科学领域:

  • 遗传学 是一个遗传学.
  • 生物统计学 生物统计学
  • 流行病学 流行病学

背景情况:

  • 门德尔随机化 (MR) 是一种流行的因果推理方法,使用遗传变异作为工具变量 (IV).
  • 在现实应用中MR方法的可靠性与潜在的混仍然不确定.
  • 现有的研究往往依赖于模拟数据,限制了实际应用.

研究的目的:

  • 为了对16种两样抽样总结级MR方法的性能进行基准测试.
  • 评估MR方法使用现实世界的遗传数据集而不是模拟.
  • 为选择合适的MR方法提供因果推理的实用指南.

主要方法:

  • 评价了16种两个样本的总结级MR方法.
  • 利用现实世界的遗传数据集进行全面的基准研究.
  • 在1000个暴露结果特征对中评估了I型错误控制,准确性,可复制性和功率.

主要成果:

  • 在不同的混场景下,MR方法的性能在不同MR方法中有显著的差异 (种群分层,繁殖,分类交配).
  • 确定了具有强大的I型错误控制和准确因果效应估计的特定方法.
  • 在评估的方法中重复性和统计能力的突出差异.

结论:

  • 选择MR方法显著影响对现实世界遗传数据的因果推理可靠性.
  • 为研究人员提供基于证据的建议,帮助他们选择合适的MR方法.
  • 推进在遗传流行病学和相关领域应用MR的最佳实践.