Computational Software for Assessing Allelic Droput

Jeremias Ivan, A. A. Parikesit
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Abstract

Allelic dropout is a failed amplification of an allele which usually happens when the concentration of the DNA sample is low. As there is a missing genotype, the result of the DNA profiling will significantly be affected. One way to overcome this problem is by using computational software that considers thedropout event within its algorithm. This review is aimed to discuss several software that have been created to serve this purpose. All of the listed software turn to implement Maximum Likelihood (LR) algorithm within their calculation; however, they use different parameters and variables. This reviewshowed that allelic dropout should not be evaluated alone; it correlates with other events in creating a low quality of DNA. Therefore, a comprehensive algorithm that consider all of the factors should be built to best estimates the allelic dropout rate within a data.
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评估等位基因产量的计算软件
等位基因缺失是一种等位基因扩增失败的现象,通常发生在DNA样本浓度较低时。由于缺失基因型,DNA分析结果将受到严重影响。克服这个问题的一种方法是使用计算软件,该软件在其算法中考虑辍学事件。这篇评论的目的是讨论为达到这个目的而创建的几个软件。所有列出的软件都转向在其计算中实现最大似然(LR)算法;然而,它们使用不同的参数和变量。这篇综述表明,等位基因缺失不应该单独评估;它与产生低质量DNA的其他事件有关。因此,应该建立一个综合考虑所有因素的综合算法,以最好地估计数据中的等位基因辍学率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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