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相关概念视频

Polygenic Traits01:18

Polygenic Traits

66.0K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.4K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.4K
Prediction Intervals01:03

Prediction Intervals

2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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Estimating Population Standard Deviation01:26

Estimating Population Standard Deviation

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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
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Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

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In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
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相关实验视频

Updated: Jul 16, 2025

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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使用从总结统计数据中获得的多基因预测过高估计的预测.

David Keetae Park1, Mingshen Chen2, Seungsoo Kim3

  • 1Department of Biomedical Engineering, Columbia University, New York, USA.

BMC genomic data
|September 14, 2023
PubMed
概括

使用总结统计数据的多基因风险评分 (PRS) 研究可能会因未经监测的样本重叠而导致结果膨胀. 通过比较PRS (rPRS) 的原始数据和PRS (sPRS) 的总结统计数据,发现高血压和身高等特征的sPRS膨胀.

关键词:
阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.复杂的遗传疾病复杂的遗传疾病.过高估计偏差是一种偏差.多基因风险评分多基因风险评分.

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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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相关实验视频

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A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
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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
  • 生物信息学是一种生物信息学.

背景情况:

  • 多基因风险评分 (PRS) 研究对于预测疾病风险至关重要.
  • 从总结统计数据 (sPRS) 推导 PRS 阻止了发现和测试集之间的独立性监测.
  • 这种缺乏独立性会导致结果膨胀,特别是在高度遗传的特征.

研究的目的:

  • 为了比较从原始遗传数据 (rPRS) 和总结统计数据 (sPRS) 来得出的PRS的性能.
  • 评估sPRS结果的潜在通货膨胀,当数据集之间的独立性不能保证时.
  • 用国际阿尔茨海默氏症基因组学项目 (IGAP) 的总结统计数据评估sPRS性能,并将其与英国生物库高血压和身高数据上的rPRS进行比较.

主要方法:

  • 对rPRS和sPRS方法的比较.
  • 使用IGAP的sPRS总结统计数据,不包括APOE.
  • 将rPRS应用于英国高血压和身高的生物库数据,确保类似的发现和测试集大小.

主要成果:

  • 来自IGAP的sPRS显示阿尔茨海默病的性能指标 (ΔAUC和ΔR2) 与预期相比膨胀.
  • 在英国生物库数据上,高血压的rPRS得出了0.0036 ± 0.0027的ΔAUC和0.0032 ± 0.0028.2的ΔR2.
  • 英国生物库的高度rPRS给出了0.029 ± 0.0037.2的ΔR2.

结论:

  • 由于可能的样本重叠,sPRS结果,特别是高血压和身高等高度遗传性特征,可能会因总结统计数据而被膨胀.
  • 在sPRS研究中无法监测数据集独立性,因此需要仔细考虑种族群体内的潜在重复.
  • 确保数据集的独立性是可靠PRS研究的基本要求,当无法验证时,强调sPRS的局限性.