Computational and Systems Biology Summer Institute
Iowa State University

Research Projects for Fellows, 2009
P08: MeDIP analysis using R

Short Title:	MeDIP analysis using R
Mentors:	Dr. Karin Dorman
Description:	MeDIP is a technique for identifying CpG methylation status in genomes. Methylation status is an epigenetic (non-genetic, but sometimes heritable) change that impacts phenotype, including disease/cancer. Here, we propose to develop methods to handle the CpG methylation status dependence structure along the genome. The dependence is caused by experimental (probe or sequence read overlap) and biological (sequential methylation) reasons. Expected results: - Build a new R package. - Develop an improved method for detecting differentially methylated CpGs.
Web Resources:	http://rumi.gdcb.iastate.edu/wiki/RotationProjects
References:	Papers to read. Jacinto, Ballestar, and Esteller (2008) Down, T. A.; Rakyan, V. K.; Turner, D. J.; Flicek, P.; Li, H.; Kulesha, E.; Grf, S.; Johnson, N.; Herrero, J.; Tomazou, E. M.; Thorne, N. P.; Bckdahl, L.; Herberth, M.; Howe, K. L.; Jackson, D. K.; Miretti, M. M.; Marioni, J. C.; Birney, E.; Hubbard, T. J. P.; Durbin, R.; Tavar, S. & Beck, S. A Bayesian deconvolution strategy for immunoprecipitation -based DNA methylome analysis. Nat Biotechnol, 2008, 26, 779-785
Suitable background skills:	Possible skills needed for or learned from this project include: - theory: (empirical) Bayesian analysis, microarray data analysis. - software: Batman, Apache, MySQL. (if Batman were our target method) - program: R (MEDME), C, JAVA.