The Simons Simplex Collection, a repository of data on 2,000 families affected by autism, is a rich source of information for epidemiologic studies. However, because the data are collected at numerous institutions using a variety of methods, detecting meaningful trends across the entire collection will require serious statistical firepower. Abba Krieger and his colleagues at the University of Pennsylvania’s Wharton School plan to undertake this arduous task. The data — collected from children with autism, their parents and unaffected siblings — include demographics, medical histories of the affected children and their families, and results of various social and intelligence tests. Krieger has assembled a team of statisticians, mathematicians, bioinformatics experts and other researchers to review the data for accuracy, standardize it, and organize it into forms that are useful for statistical analyses. The researchers propose to comb the data for relationships between autism and demographic and environmental variables, and explore associations between data from the affected children and their family members. The researchers also plan to look for ‘clusters’ of individuals with similar data, which might provide insight into the variety of disorders that make up the autism spectrum. The analyses may also turn up variables or combinations of variables that are useful in predicting disease outcomes. Besides contributing to the understanding of autism and its causes, findings from this study may lead to the development of new statistical tools, and applications for handling large and diverse collections of data.