The genetic make-up and physiological state of a cell or tissue in an organism interact to determine the level at which specific genes are expressed. Identifying genes differentially expressed between 2 genetic or physiological states often gives insight into the molecular mechanisms controlled by the process in question. Various methods have been devised to identify differentially expressed genes and to quantify the expression of differentially regulated genes at the RNA or protein level. These methods are most accurate when the experimental samples are derived from highly controlled and reproducible sources, such as cultured cells. However, no simple in vitro models have been developed to study all biological processes and some are still best studied in the context of the whole organism. Using bone fracture healing as a model, we quantified the expression of 2 housekeeping and 2 regulatory genes during this complex biological process to determine the statistical parameters required to study differential gene expression in tissue samples derived from entire organisms. Our analysis shows that 5 samples in each group are needed to identify genes differentially expressed by a factor of 3 between 2 physiological or genetic states.