New algorithms for Luria-Delbruck fluctuation analysis
New algorithms for Luria-Delbruck fluctuation analysis
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DOI：
10.1016/j.mbs.2005.03.011
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发表时间：
2005-08-01
影响因子：
4.3
通讯作者：
Zheng, Q
中科院分区：
文献类型：
--
作者：
Zheng, Q
波动分析是估算微生物突变率最广泛使用的方法。突变率的点和区间估计方法的发展长期以来一直受到阻碍，缺乏封闭形式的表达在一个平行的文化突变体的数量的概率质量函数。本文使用序列卷积推导出精确的算法来计算得分函数和观察到的Fisher信息，从而有效地计算最大似然估计和基于轮廓似然的置信区间，以预测试管中发生的突变数量。这些算法及其在萨尔瓦多2.0中的实现方便了从事突变研究的生物学家在波动分析中常规使用现代统计技术。(c)2005年爱思唯尔公司All rights reserved.
Fluctuation analysis is the most widely used approach in estimating microbial mutation rates. Development of methods for point and interval estimation of mutation rates has long been hampered by lack of closed form expressions for the probability mass function of the number of mutants in a parallel culture. This paper uses sequence convolution to derive exact algorithms for computing the score function and observed Fisher information, leading to efficient computation of maximum likelihood estimates and profile likelihood based confidence intervals for the expected number of mutations occurring in a test tube. These algorithms and their implementation in SALVADOR 2.0 facilitate routine use of modern statistical techniques in fluctuation analysis by biologists engaged in mutation research. (c) 2005 Elsevier Inc. All rights reserved.