Application of public-domain statistical analysis software for evaluation and comparison of comet assay data

Abstract

A novel approach for statistical analysis of comet assay data (i.e.: tail moment) is proposed, employing public-domain statistical software, the R system. The analytical strategy takes into account that the distribution of comet assay data, like the tail moment, is usually skewed and do not follow a normal distribution. Probability distributions used to model comet assay data included: the Weibull, the exponential, the logistic, the normal, the log normal and log-logistic distribution. In this approach it was also considered that heterogeneity observed among experimental units is a random feature of the comet assay data. This statistical model can be characterized with a location parameter m ij , a scale parameter r and a between experimental units variability parameter θ. In the logarithmic scale, the parameter m ij depends additively on treatment and random effects, as follows: log ( m i j ) = a 0 + a 1 x i j + b i , where exp( a 0) represents approximately the mean value of the control group, exp( a 1) can be interpreted as the relative risk of damage with respect to the control group, x ij is an indicator of experimental group and exp( b i ) is the individual risk effects assume to follows a Gamma distribution with mean 1 and variance θ. Model selection is based on Akaike's information criteria (AIC). Real data coming from comet analysis of blood samples taken from the flounder Paralichtys orbignyanus (Teleostei: Paralichtyidae) and from samples of cells suspension obtained from the estuarine polychaeta Laeonereis acuta (Nereididae) were employed. This statistical approach showed that the comet assay data should be analyzed under a modeling framework that take into account the important features of these measurements. Model selection and heterogeneity between experimental units play central points in the analysis of these data.