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相关概念视频

Genome-wide Association Studies-GWAS01:11

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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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Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
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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.
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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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The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
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Infinium Assay for Large-scale SNP Genotyping Applications
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对全基因组关联研究的基于人口意识的突变的显著性值.

Maura John1,2, Arthur Korte3, Marco Todesco4,5,6

  • 1Technical University of Munich, TUM Campus Straubing for Biotechnology and Sustainability, Bioinformatics, 94315 Straubing, Germany.

Bioinformatics advances
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概括

permGWAS2通过在 permutation 测试和优化计算过程中保持种群结构来改进全基因组关联研究 (GWAS). 这种方法减少了错误的发现,并在复杂的种群中确定了新的特征关联.

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科学领域:

  • 遗传学 是一个遗传学.
  • 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:

  • 基于突变的显著性值在全基因组关联研究 (GWAS) 中为邦费罗尼校正提供了强大的替代方案,特别是在偏斜的表型分布中.
  • GWAS方法引入了高效的批量计算,但遭受了冗余计算和破坏人口结构的损害.
  • 传统的换方法只能换表型,可以打破底层的人口结构,导致不准确的结果.

研究的目的:

  • 开发一种改进的基于 permutation 的 GWAS 方法 (permGWAS2),以保持人口结构并优化计算效率.
  • 减少冗余计算,提高GWAS中的显著性值的准确性.
  • 识别具有适应性特征的新型遗传关联,并过出错误阳性.

主要方法:

  • 实现了permGWAS2,这是一种利用块矩阵分解进行优化排列计算的新方法.
  • 在整个变种过程中保留了种群结构,与传统方法不同.
  • 在合成数据集上验证了permGWAS2,并重新分析了86个表型特征的野生向日 (Helianthus annuus L.) 数据集.

主要成果:

  • 与合成数据上的 permGWAS 和 Bonferroni 校正相比,permGWAS2 在歪曲的表型中表现出较低的错误发现率.
  • 对野生向日数据集的分析发现了许多具有假定适应性特征的新兴关联.
  • 之前报告的几种可能的假阳性关联被成功删除,从而增加了对研究结果的信心.

结论:

  • 通过保持人口结构和提高计算效率,permGWAS2为GWAS方法提供了显著的进步.
  • 该方法提供了更准确的显著性值,从而更可靠地识别遗传关联.
  • permGWAS2是一个有价值的开源工具,用于遗传研究,特别是对复杂的人口结构和倾斜的表型的研究.