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X. Lin 199skills through seminars, workshops and projects to enable our trainees to meetmodern challenges for conducting translational genomic research.18.6 Concluding remarksWe are living in an exciting time of genetic and genomic science, where massive’omics data present statisticians with many opportunities and challenges. Totake a full advantage of the opportunities and meet the challenges, we needto strategically broaden our roles and quantitative and scientific knowledge,so that we can play a quantitative leadership role as statistical genetic andgenomic scientists in both method development and scientific discovery. It isimportant to develop new strategies to train our students along these linesso they can succeed in the increasingly interdisciplinary research environmentwith massive data. With the joint effort of our community, we can best positionourselves and the younger generation as quantitative leaders for new scientificdiscovery in the ’omics era.ReferencesBansal, V., Libiger, O., Torkamani, A., and Schork, N.J. (2010). Statisticalanalysis strategies for association studies involving rare variants. NatureReviews Genetics,11:773–785.Breslow, N.E. and Clayton, D.G. (1993). Approximate inference in generalizedlinear mixed models. Journal of the American Statistical Association,88:9–25.Cirulli, E.T. and Goldstein, D.B. (2010). Uncovering the roles of rare variantsin common disease through whole-genome sequencing. Nature ReviewsGenetics, 11:415–425.Dickson, S.P., Wang, K., Krantz, I., Hakonarson, H., and Goldstein, D.B.(2010). Rare variants create synthetic genome-wide associations. PLoSBiology, 8:e1000294, doi:10.1371/journal.pbio.1000294.Hung, R.J., McKay, J.D., Gaborieau, V., Boffetta, P., Hashibe, M., Zaridze,D., Mukeria, A., Szeszenia-Dabrowska, N., Lissowska, J., Rudnai, P., Fabianova,E., Mates, D., Bencko, V., Foretova, L., Janout, V., Chen, C.,Goodman, G., Field, J.K., Liloglou, T., Xinarianos, G., Cassidy, A. et al(2008). A subunit genes on 15q25. Nature, 452:633–637.