Department of Epidemiology and Biostatistics, Texas A &M School of Public Health, College Station, TX, 77843, USA.
Genetica. 2023 Dec;151(6):369-373. doi: 10.1007/s10709-023-00200-1. Epub 2023 Nov 27.
The fluctuation experiment, devised by Luria and Delbrück in 1943, remains the method of choice for measuring microbial mutation rates in the laboratory. While most inference problems commonly encountered in a fluctuation experiment can be tackled by existing standard algorithms, investigators from time to time run into nonstandard problems not amenable to any existing algorithms. A major obstacle to solving these nonstandard problems is the construction of confidence intervals for mutation rates. This note describes methods for two important categories of nonstandard problems, namely, pooling data from separate experiments and analyzing grouped mutant count data, focusing on the construction of likelihood ratio confidence intervals. In addition to illustrative examples using real-world data, simulation results are presented to help assess the proposed methods.
波动实验由 Luria 和 Delbrück 于 1943 年设计，至今仍是实验室测量微生物突变率的首选方法。虽然波动实验中常见的大多数推断问题都可以通过现有的标准算法来解决，但研究人员不时会遇到无法使用任何现有算法解决的非标准问题。解决这些非标准问题的主要障碍是突变率置信区间的构建。本说明介绍了两种重要的非标准问题类别，即从单独的实验中汇总数据和分析分组突变体计数数据，重点是似然比置信区间的构建。除了使用实际数据的说明性示例外，还提供了模拟结果来帮助评估所提出的方法。
