Statistical design and analysis of mutation studies in transgenic mice

Abstract

We have been working on identifying sources of variability in data from transgenic mouse mutation assays in order to develop appropriate statistical methods and designs for routine studies. Data from our lab and elsewhere point to the presence of significant animal-to-animal variability, which must be taken into account in statistical hypothesis tests. Here, the usual Cochran-Armitage (CA) test for trend in mutant frequencies, which takes the transgene as the experimental unit, and a generalized Cochran-Armitage test (GCA), which takes the animal as the experimental unit, are contrasted in computer simulations that help to quantify the differences between these statistical tests. The simulations report the statistical power of each test to detect treatment group differences, and their type I error rates. We find in general that the GCA test performs poorly compared to the CA test when it is appropriate to take the transgene as the experimental unit, and the study also uses a small number of animals. However, the CA test performs poorly in small group-size studies when the animal is the appropriate experimental unit. Extensions of the computer simulations allow for identification of cost-effective experimental designs. The results emphasize that the benefits of using additional animals in these mutation studies can be realized without substantial increases in costs. Here we illustrate the methods for liver studies in our lab. These methods can be used to derive optimal experimental designs for any combination of spontaneous mutant frequency and animal-to-animal variability.

Mutational specificity: Mutational spectra in transgenic animal research: Data analysis and study design based upon the mutant or mutation frequency

“…However, it is questionable whether sufficient data exist to adequately address the sources of variability issue in mutational spectra and its implication on the statistical evaluation. It is worth noting that methods described in Carr and Gorelick [1995], which are applicable to the overall mutant frequency data, can easily be extended to the category-specific MF data if animal variability were found to be important.…”

Sex‐specific induction of mutations by PhIP in the kidney of male and female rats and its modulation by conjugated linoleic acid

“…The rats were weighed weekly and the food consumed was measured twice weekly. Male and female rats were divided into eight groups, each consisting of 4 -6 rats, consistent with statistical recommendations by Carr and Gorelick [1995]. When the rats were 50 days old, 100 ppm PhIP (Ͼ98% HPLC pure, Toronto Research Chemicals, Toronto, Canada) were incorporated into the diet.…”

Detection of mutations in transgenic fish carrying a bacteriophage λ cII transgene target

“…Statistical analyses revealed that as few as 6-7 animals were required to detect a 50% induction above background (3 ϫ 10 Ϫ5 ), and 2-3 animals were required to detect a 100% induction (power ϭ 0.80, ␣ ϭ 0.05). A total of 5-10 animals͞treatment are recommended in transgenic rodent assays to give similar power of detection (16,17). To determine whether the cII gene in the fish was responsive to chemical mutagen exposure, we measured mutant frequencies in fish 15 days after exposure to 0, 60, or 120 mg͞liter ENU.…”

“…To verify mutant cII phenotypes, plaques (30-100% total plaques) were cored, incubated in SM buffer (0.1 M NaCl͞0.01 M MgSO 4 ͞0.05 M Tris⅐HCl, pH 7.5͞0.01% gelatin) at room temperature for 1 h, and replated at low density under selective conditions. The minimum number of animals required to detect a significant induction of mutations was estimated by using a spontaneous mutant frequency of 3 ϫ 10 Ϫ5 , recovery of Ͼ300,000 pfu per animal, a power of 0.80, and ␣ ϭ 0.05 (16,17). Comparisons of mutation frequencies were tested for significance by using the generalized Cochran-Armitage test.…”