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Anil Ori: Integration of longitudinal gene expression with polygenic disease risk establishes human neuronal differentiation as a model to study schizophrenia

Date:July 7, 2017Posted By:Duke Hong
Anil Ori: Integration of longitudinal gene expression with polygenic disease risk establishes human neuronal differentiation as a model to study schizophrenia

07/07/2017 @ 13:10-13:40
Retreat Research Talk by Anil Ori
Integration of longitudinal gene expression with polygenic disease risk establishes human neuronal differentiation as a model to study schizophrenia
1. Tai, Y.C. and Speed, T.P., 2006. A multivariate empirical Bayes statistic for replicated microarray time course data. The Annals of Statistics, 34(5), pp.2387-2412.
2. Aryee, M.J., GutiƩrrez-Pabello, J.A., Kramnik, I., Maiti, T. and Quackenbush, J., 2009. An improved empirical bayes approach to estimating differential gene expression in microarray time-course data: BETR (Bayesian Estimation of Temporal Regulation). BMC bioinformatics, 10(1), p.409.
3. Finucane, H.K., Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.R., Anttila, V., Xu, H., Zang, C., Farh, K. and Ripke, S., 2015. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nature genetics, 47(11), pp.1228-1235.
4. de Leeuw, C.A., Mooij, J.M., Heskes, T. and Posthuma, D., 2015. MAGMA: generalized gene-set analysis of GWAS data. PLoS computational biology, 11(4), p.e1004219.

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Funded by NIH since 2016 – Grant GM112625

IN PARTNERSHIP WITH EDMOND J. SAFRA CENTER FOR BIOINFORMATICS:

AND THE ARTIFICIAL INTELLIGENCE/MACHINE LEARNING CONSORTIUM TO ADVANCE HEALTH EQUITY AND RESEARCHER DIVERSITY (AIM-AHEAD):

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