基于 Ma-Sandri-Sarkar 最大似然法计算波动检测结果和 95% 置信区间的 R 代码

IF 1.3 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Ola Abdalla , Cameron Walker , Koichiro Ishimori
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引用次数: 0

摘要

卢里亚-德尔布吕克波动测定法是计算突变率的重要实验,尤其是在遗传和突变研究中。它的可靠性和准确性使其成为众多研究人员的首选方法。在这篇文章中,我们提供了一个 R 代码,可以更轻松地对测定结果进行统计分析,并提供了基于黄金标准方法 "Ma-Sandri-Sarkar 最大似然法" 计算 95% 置信区间的最具挑战性的代码。最近,通过 R 中的优化函数最大化似然函数是一项具有挑战性的任务。众所周知,似然函数的递归格式会导致内存堆栈问题。我们的研究结果表明,利用该函数的非递归版本可以提高最大化过程的可操作性。有了这套代码,未来的科学家就能获得与驱动遗传变异的生物机制有关的宝贵统计见解,从而有助于开发新型治疗干预措施和创新解决方案,应对各种生物和医学挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

R-code for calculating fluctuation assay results and 95% confidence intervals based on Ma–Sandri–Sarkar Maximum Likelihood

R-code for calculating fluctuation assay results and 95% confidence intervals based on Ma–Sandri–Sarkar Maximum Likelihood

The Luria–Delbrück fluctuation assay is an essential experiment in calculating mutation rates, especially in genetic and mutation research. Its reliability and accuracy have made it the go-to method for numerous researchers. In this article, we provide an R-code that statistically analyzes the assay results more easily and offers the most challenging code for calculating 95% confidence intervals based on the gold standard method “Ma–Sandri–Sarkar Maximum Likelihood.” Recently, the maximization of the likelihood function through optimization functions in R can be a challenging task. The recursive format of the likelihood function is known to cause memory stack issues. Our findings indicate that utilizing a non-recursive version of the function can increase the tractability of the maximization process. With this code, future scientists can unlock valuable statistical insights related to the biological mechanisms that drive genetic variation and can, therefore, contribute to developing novel therapeutic interventions and innovative solutions to various biological and medical challenges.

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来源期刊
Software Impacts
Software Impacts Software
CiteScore
2.70
自引率
9.50%
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0
审稿时长
16 days
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