The Ames Salmonella/Microsome Mutagenicity Assay: Issues of Inference and Validation

Abstract

The importance of chemically induced mutation for human health is discussed briefly, and the biological basis for the primary in vitro assay for mutagenicity, the Ames Salmonella/microsome assay, is reviewed. A previous analysis for Ames test data, based on two mathematical models of the competing risks of mutation and toxicity, is shown to have inflated false-positive rates. A reason for this is the existence of local singularities in the Fisher information matrix. A new likelihood ratio test incorporating a pretest of a nuisance parameter is proposed, and its size is validated with replicated experimental data through an analysis based on a finite-mixture-of-binomials model.

Key Words:

• EM algorithm
• Finite mixture of binomials
• Identifiability
• Likelihood ratio tests
• Maximum likelihood estimates