Ycart Bernard, Veziris Nicolas
Laboratoire Jean Kuntzmann, Univ. Grenoble Alpes, Grenoble, France; Laboratoire d'Excellence "TOUCAN" (Toulouse Cancer), Toulouse, France.
Sorbonne Universités, UPMC Univ. Paris 06, CR7, Centre d'Immunologie et des Maladies Infectieuses, CIMI, Team E13 (Bacteriology), Paris, France; INSERM, U1135, Centre d'Immunologie et des Maladies Infectieuses, CIMI, Team E13 (Bacteriology), Paris, France; AP-HP, Hôpital Pitié-Salpêtrière, Centre National de Référence des Mycobactéries et de la Résistance des Mycobactéries aux Antituberculeux, Laboratoire de Bactériologie-Hygiène, Paris, France; Mycobacteria Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, United States of America.
PLoS One. 2014 Jul 2;9(7):e101434. doi: 10.1371/journal.pone.0101434. eCollection 2014.
Estimation methods for mutation rates (or probabilities) in Luria-Delbrück fluctuation analysis usually assume that the final number of cells remains constant from one culture to another. We show that this leads to systematically underestimate the mutation rate. Two levels of information on final numbers are considered: either the coefficient of variation has been independently estimated, or the final number of cells in each culture is known. In both cases, unbiased estimation methods are proposed. Their statistical properties are assessed both theoretically and through Monte-Carlo simulation. As an application, the data from two well known fluctuation analysis studies on Mycobacterium tuberculosis are reexamined.
在卢里亚-德尔布吕克波动分析中，突变率（或概率）的估计方法通常假定从一种培养物到另一种培养物，最终细胞数保持恒定。我们表明，这会导致系统性地低估突变率。我们考虑了关于最终细胞数的两个层次的信息：一是变异系数已被独立估计，二是每种培养物中的最终细胞数是已知的。在这两种情况下，我们都提出了无偏估计方法。我们从理论上以及通过蒙特卡洛模拟评估了它们的统计特性。作为一个应用，我们重新审视了两项关于结核分枝杆菌的著名波动分析研究的数据。
