Needles in the haystack: identifying individuals present in pooled genomic data.
Needles in the haystack: identifying individuals present in pooled genomic data.
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DOI：
10.1371/journal.pgen.1000668
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发表时间：
2009-10
期刊：
影响因子：
4.5
通讯作者：
Buetow K
中科院分区：
文献类型：
--
作者：
Braun R;Rowe W;Schaefer C;Zhang J;Buetow K
最近的出版物描述并应用了一种新的度量方法，该度量方法量化了个体相对于两个群体样本的遗传距离，并建议该度量方法使得在仅知道其边际等位基因频率的样本中推断具有已知基因的个体的存在成为可能。然而，这一指标的假设、限制和效用仍未完全确定。在这里，我们使用公开可获得的基因类型对该方法进行了实证测试，并对该方法的优点和局限性进行了分析研究。结果表明，零分布对基本假设很敏感，因此很难准确地校准将个人归类为总体样本的阈值。因此，在实践中获得的假阳性率比之前认为的要高得多。然而，尽管该指标在识别样本中个人的存在方面存在不足，但我们的结果表明，未来将该方法调整为祖先推断或疾病预测问题的潜在研究途径。通过揭示提出的方法的优点和局限性，我们希望阐明在哪些情况下可以以适当的方式使用该距离度量。我们还讨论了我们的发现在取证应用和保护GWA参与者隐私方面的意义。在这份报告中，我们评估了最近发表的一种方法，用于确定个体是否存在于复杂的基因组DNA混合物中。基于这样一种直觉，即一个人在基因上更接近于一个包含他的样本，而不是一个不包含他的样本，这里研究的方法使用距离度量来量化一个个人相对于两个总体样本的相似性。尽管这种方法的初步应用显示了一个有希望的假阴性率，但假设的零分布(因此是真实的假阳性率)的准确性仍然没有被研究；在这里，我们解析地探索这个问题，并描述这种方法的测试，以评估不在混合物中的个人被错误地归类为成员的可能性。我们的结果表明，由于该方法对潜在假设的敏感性，该方法在实践中具有很高的假阳性率，限制了其在推断群体中个人的存在方面的有效性。通过揭示提出的方法的优点和局限性，我们阐明了这种距离度量可以在取证和医疗隐私政策中以适当的方式使用的情况。
Recent publications have described and applied a novel metric that quantifies the genetic distance of an individual with respect to two population samples, and have suggested that the metric makes it possible to infer the presence of an individual of known genotype in a sample for which only the marginal allele frequencies are known. However, the assumptions, limitations, and utility of this metric remained incompletely characterized. Here we present empirical tests of the method using publicly accessible genotypes, as well as analytical investigations of the method's strengths and limitations. The results reveal that the null distribution is sensitive to the underlying assumptions, making it difficult to accurately calibrate thresholds for classifying an individual as a member of the population samples. As a result, the false-positive rates obtained in practice are considerably higher than previously believed. However, despite the metric's inadequacies for identifying the presence of an individual in a sample, our results suggest potential avenues for future research on tuning this method to problems of ancestry inference or disease prediction. By revealing both the strengths and limitations of the proposed method, we hope to elucidate situations in which this distance metric may be used in an appropriate manner. We also discuss the implications of our findings in forensics applications and in the protection of GWAS participant privacy. In this report, we evaluate a recently-published method for resolving whether individuals are present in a complex genomic DNA mixture. Based on the intuition that an individual will be genetically “closer” to a sample containing him than to a sample not, the method investigated here uses a distance metric to quantify the similarity of an individual relative to two population samples. Although initial applications of this approach showed a promising false-negative rate, the accuracy of the assumed null distribution (and hence the true false-positive rate) remained uninvestigated; here, we explore this question analytically and describe tests of this method to assess the likelihood that an individual who is not in the mixture is mistakenly classified as being a member. Our results show that the method has a high false-positive rate in practice due to its sensitivity to underlying assumptions, limiting its utility for inferring the presence of an individual in a population. By revealing both the strengths and limitations of the proposed method, we elucidate situations in which this distance metric may be used in an appropriate manner in forensics and medical privacy policy.
影响因子：
4.5
作者：
Homer N;Szelinger S;Redman M;Duggan D;Tembe W;Muehling J;Pearson JV;Stephan DA;Nelson SF;Craig DW
通讯作者：
Craig DW
DOI：
10.1007/s13318-025-00934-7
发表时间：
2025-02-12
影响因子：
2.400
作者：
Luigi La Via;Andrea Marino;Giuseppe Cuttone;Giuseppe Nunnari;Cristian Deana;Manfredi Tesauro;Antonio Voza;Raymond Planinsic;Yaroslava Longhitano;Christian Zanza
通讯作者：
Christian Zanza