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.

Public Health Relevance

The purpose of this project is to develop new statistical and computational tools for analyzing and interpreting data from the ENCODE project. These data relate to the controls of gene regulation in a wide variety of cell types.

Agency
National Institute of Health (NIH)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01HG007036-04
Application #
8701329
Study Section
Special Emphasis Panel (ZHG1)
Program Officer
Gilchrist, Daniel A
Project Start
Project End
Budget Start
Budget End
Support Year
4
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Stanford University
Department
Genetics
Type
Schools of Medicine
DUNS #
City
Stanford
State
CA
Country
United States
Zip Code
94304
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