We propose to develop statistical and computational methods for interpreting data on gene regulation in a variety of cell types from the ENCODE Project. Our work will focus on (i) developing methods for integrating diverse data types in many tissues to infer chromatin architecture; (ii) inferring the sequence determinants and regulatory consequences of differences in chromatin across cell types; and (iii) empirical tests of our predictions using both natural genetic variation and experimental approaches.
|Banovich, Nicholas E; Lan, Xun; McVicker, Graham et al. (2014) Methylation QTLs are associated with coordinated changes in transcription factor binding, histone modifications, and gene expression levels. PLoS Genet 10:e1004663|
|Raj, Anil; Stephens, Matthew; Pritchard, Jonathan K (2014) fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197:573-89|
|Nalabothula, Narasimharao; McVicker, Graham; Maiorano, John et al. (2014) The chromatin architectural proteins HMGD1 and H1 bind reciprocally and have opposite effects on chromatin structure and gene regulation. BMC Genomics 15:92|
|McVicker, Graham; van de Geijn, Bryce; Degner, Jacob F et al. (2013) Identification of genetic variants that affect histone modifications in human cells. Science 342:747-9|