New algorithms for Luria-Delbrck fluctuation analysis. Academic Article

abstract

• 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.

authors

• Zheng, Qi

published proceedings

• Math Biosci

author list (cited authors)

• Zheng, Q. i.

citation count

• 46

complete list of authors

• Zheng, Qi

publication date

• January 2005

publisher

• Elsevier  Publisher

published in

• Mathematical Biosciences  Journal

keywords

• Algorithms
• Computer Simulation
• Escherichia Coli
• Likelihood Functions
• Models, Genetic
• Mutation

Digital Object Identifier (DOI)

• 10.1016/j.mbs.2005.03.011

start page

• 198

end page

• 214

volume

• 196

issue

• 2

URL

• https://www.scopus.com/inward/record.uri?eid=2-s2.0-23044450296&partnerID=40&md5=c0476cae556a24522c4e880d4ed94e05