HOUSTON, March 22, 2007 -- More powerful computers are allowing scientists and engineers to conduct simulations that grow more realistic each year. While companies are using these tools to slash the costs of producing everything from airliners to antibiotics, researchers in Houston are using them to refine their search for the genetic causes of disease.
In a new study published today in the journal PLoS Genetics, statisticians and genetic epidemiologists from Rice University and The University of Texas M. D. Anderson Cancer Center used computer simulations to trace genetic changes over thousands of generations in a simulated population of hundreds of thousands of people. The goal: find out whether the tools that statistical geneticists use to pinpoint disease genes are up to the task of identifying multiple genes that cause complex diseases like cancer.
"In a real population, you never have the complete genetic picture, particularly for complex diseases where more than one gene is implicated and where environmental factors play a role," said lead author Bo Peng of M. D. Anderson. "If we only see the people who get sick, we can never be sure how many people with the disease variant of the gene avoided getting sick. And there's always the question about how many people got the disease even though they didn't carry the variant."
In order to simulate the evolution of complex human diseases, Peng developed a computer program called simuPOP that generates genetic profiles for large multi-generation populations. The program, which Peng developed during his doctoral studies at Rice, allows researchers to sample individuals from a simulated population and test whether statistical methods are up to the task of accurately identifying genes that interact to cause complex diseases.
"Though they have much in common, the disciplines of statistical genetics, population genetics, molecular genetics and genetic epidemiology have traditionall