Many in vivo experiments with mice involve four groups. For example, in oncology models often there are two treatments (one experimental and one standard of care) that are given alone, jointly, and then compared to a vehicle control. The standard analysis for this type of experiment appears to be a two-way ANOVA test.
However, in my case the experimental design is quite different and with it the hypothesis to be tested. I also have four groups of mice with two independent factors. Here, one is a treatment that induces a disease state while the other is the mutational status of a gene. My hypothesis, based on a variety of additional data points, is that the mutation in the gene will suppresses the disease.
It was suggested to me that, as above, I should perform a two-way ANOVA to analyze the data. However, I believe that in this case the untreated animals are merely a control to show that my disease-causing intervention is working as expected. In fact, the only comparison I am interested in is between the wild type and mutation group of mice that were treated to induce the disease. Furthermore, my hypothesis is that the gene will suppress the disease (and not merely affect it in an unknown direction).
So my contention is that the 'correct' test in this case would be a simple one-tailed student's t-test between the wild type and mutant group of mice on the disease-inducing treatment.