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

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 theta. In the logarithmic scale, the parameter m(ij) depends additively on treatment and random effects, as follows: log(m(ij)) = a0 + a1x(ij) + b(i), where exp(a0) represents approximately the mean value of the control group, exp(a1) 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 theta. 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.