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相关概念视频

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.4K
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...
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Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

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Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.5K
Wilcoxon Signed-Ranks Test for Median of Single Population01:14

Wilcoxon Signed-Ranks Test for Median of Single Population

101
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...
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One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

5.7K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
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Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

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Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
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One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

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One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
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相关实验视频

Updated: Jun 5, 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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[全基因组关联研究中的极度不平衡数据的统计方法 (1) ]

N Xie1, W J Bi2, Z W Zhang1

  • 1Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing211166, China.

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
|December 4, 2024
PubMed
概括

经典的统计方法在极度不平衡的数据上失败,这在全基因组关联研究 (GWAS) 中很常见. 这可能导致由于I型错误的通货膨胀或通货紧缩导致不准确的结果,需要新的遗传统计方法.

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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

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Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
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相关实验视频

Last Updated: Jun 5, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

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科学领域:

  • 遗传学 遗传学 是一个
  • 生物统计学 生物统计学
  • 统计遗传学 统计遗传学

背景情况:

  • 极度不平衡的数据,以偏差比例为特征 (例如,疾病发病率低,罕见变异),在统计分析中带来了挑战.
  • 经典的统计方法,如逻辑回归和考克斯模型,可能会产生不可靠的结果.

研究的目的:

  • 突出经典统计方法的局限性,当它们应用于遗传统计中的极度不平衡的数据集时.
  • 为了应对对不平衡数据的全基因组关联研究 (GWAS) 强有力的统计方法的日益增长的需求.

主要方法:

  • 引入与遗传统计相关的经典统计方法.
  • 模拟实验以证明使用极度不平衡数据的经典方法的失败.

主要成果:

  • 经典的统计方法在处理极度不平衡的数据时可能会偏离理论分布.
  • 第一种类型的错误率可以被膨胀或降低,从而损害假设测试的准确性.

结论:

  • 研究人员必须意识到在GWAS中使用古典统计方法对极度不平衡数据的陷.
  • 发展和应用先进的统计技术来分析不平衡的遗传数据集至关重要.