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.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
7U01HG007036-03
Application #
8791956
Study Section
Special Emphasis Panel (ZHG1-HGR-M (M2))
Program Officer
Pazin, Michael J
Project Start
2012-09-17
Project End
2015-06-30
Budget Start
2013-07-03
Budget End
2014-06-30
Support Year
Fiscal Year
2013
Total Cost
$346,990
Indirect Cost
$125,377
Name
Stanford University
Department
Genetics
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
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