"Complex diseases like hypertension and cancer are usually caused by multiple disease-susceptibility genes, environmental factors and interactions between environmental and genetic factors," said co-author Christopher Amos, professor of epidemiology at M. D. Anderson. "In the current study, we show that our method of simulating populations as they move forward in time, over multiple generations, is a practical and useful approach for simulating complex diseases."
Peng said the latest findings are preliminary but they confirm that known statistical genetic methods are limited in their ability to accurately identify the genetic interactions implicated in complex diseases. Peng said the findings are useful because they identify which methods work best with particular types of populations. He said simuPOP could be useful in developing and testing new methods for gene mapping, and he's already gotten interest from more than 20 research groups that are interested in using the program.