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相关概念视频

Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

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Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
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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.
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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.
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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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    这项研究引入了AE-TWAS,一种新的方法,使用自编码器拒绝转录组数据,以改善基因表达遗传性. 这种增强增强了转录组范围的关联研究 (TWAS) 的性能,以更好地绘制基因型-表型映射.

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    科学领域:

    • 基因组学就是基因组学.
    • 生物信息学是一种生物信息学.
    • 系统生物学 系统生物学

    背景情况:

    • 全转录组关联研究 (TWAS) 使用基因表达数据将遗传变异与表型特征联系起来.
    • 预测基因表达对TWAS至关重要,但许多基因的低遗传性限制了模型性能.
    • 现有的TWAS方法在基因表达数据中的噪音和非线性问题上扎.

    研究的目的:

    • 提出AE-TWAS,这是一种新的方法,通过在分析之前拒绝转录组数据来增强TWAS.
    • 改善基因表达数据的遗传性和连接性,以便更准确地绘制基因型-表型关联映射.
    • 通过改进的TWAS来识别疾病的功能相关基因.

    主要方法:

    • 开发了AE-TWAS,在标准TWAS之前结合了基于自动编码器 (AE) 的数据转换步骤.
    • 将转录组分为共同表达模块,并使用AE重建每个模块内的数据,有效地消除噪声.
    • 将转换后的数据应用于下游TWAS进行基因型-表型关联分析.

    主要成果:

    • AE-TWAS转换显著增加表达遗传性,特别是在最初遗传性较低的基因中.
    • 无效转录组数据显示,在共同表达模块内增强了连接性.
    • AE-TWAS改善了TWAS的性能,并确定了具有更大的功能意义的与疾病相关的枢纽基因.

    结论:

    • AE-TWAS有效地否定转录组数据,增强基因表达遗传性和模块连接性.
    • 拟议的方法提高了TWAS对基因型-表型关联研究的准确性和功率.
    • AE-TWAS促进了功能相关基因和潜在疾病生物标志物的发现.