DATA MANAGEMENT AND ANALYSIS CORE (DMAC): The DMAC will manage and store all relevant research data and provide data analytic support for all projects in COGEND. Our overall aims are to: 1) Maintain a database containing all instruments administered in COGEND, derived measures such as diagnoses, Fagerstrom scores and indices of nicotine consumption. 2) Provide well-documented, cleaned copies of all data sets to COGEND investigators on a regular basis and distribute data to investigators external to COGEND in accordance with agreed-upon procedures for sharing. Provide support and expertise in investigating the data contained in all data sets to COGEND and accepted non-COGEND investigators. 3) Maintain a web site for COGEND investigators. Access will require a sign-on and password. 4) Maintain data sets containing the genotypic data from the molecular genetics component of COGEND and data files describing the SNP markers. We will provide automated cleaning programs to check for genotyping errors, and provide an interface using a genome browser for annotation. 5) Maintain a dynamic process to provide oversight and support for the data analyses of the individual COGEND projects. The Data Analysis Committee will work with project investigators to provide formatted data for analysis, recommend analysis protocols to the individual projects, and supply expertise in necessary methodologic areas. These latter would include recommendations for dealing with multiple testing, prioritization and design of follow-up experiments, and advice on statistical techniques. 6) Transmit data to the NIDA Genetics Repository for sharing with the wider scientific community. The COGEND data represent a unique resource. The sample size is large enough to provide significant power to test the primary hypotheses. Moreover, one of the most important aims of COGEND is to make these resources available to the broader scientific community. This will be done in a way to permit alternative analyses for phenotypic classification, testing of new candidate genes, or testing integrative hypotheses across several domains.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA089392-10
Application #
8381043
Study Section
Special Emphasis Panel (ZCA1-RPRB-7)
Project Start
Project End
2014-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
10
Fiscal Year
2012
Total Cost
$172,487
Indirect Cost
$37,387
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Mercati, O; Huguet, G; Danckaert, A et al. (2017) CNTN6 mutations are risk factors for abnormal auditory sensory perception in autism spectrum disorders. Mol Psychiatry 22:625-633
Wang, Jian; Talluri, Rajesh; Shete, Sanjay (2017) Selection of X-chromosome Inactivation Model. Cancer Inform 16:1176935117747272
Teitelbaum, A M; Murphy, S E; Akk, G et al. (2017) Nicotine dependence is associated with functional variation in FMO3, an enzyme that metabolizes nicotine in the brain. Pharmacogenomics J :
Zhang, Tian-Xiao; Saccone, Nancy L; Bierut, Laura J et al. (2017) Targeted sequencing identifies genetic polymorphisms of flavin-containing monooxygenase genes contributing to susceptibility of nicotine dependence in European American and African American. Brain Behav 7:e00651
Singh, Tarjinder; Walters, James T R; Johnstone, Mandy et al. (2017) The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nat Genet 49:1167-1173
Peckham-Gregory, Erin C; Chakraborty, Rikhia; Scheurer, Michael E et al. (2017) A genome-wide association study of LCH identifies a variant in SMAD6 associated with susceptibility. Blood 130:2229-2232
Hancock, D B; Guo, Y; Reginsson, G W et al. (2017) Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence. Mol Psychiatry :
Wang, Minghui; Huang, Jianfei; Liu, Yiyuan et al. (2017) COMBAT: A Combined Association Test for Genes Using Summary Statistics. Genetics 207:883-891
Taylor, Kimberly E; Wong, Quenna; Levine, David M et al. (2017) Genome-Wide Association Analysis Reveals Genetic Heterogeneity of Sjögren's Syndrome According to Ancestry. Arthritis Rheumatol 69:1294-1305
Hartz, Sarah M; Horton, Amy C; Oehlert, Mary et al. (2017) Association Between Substance Use Disorder and Polygenic Liability to Schizophrenia. Biol Psychiatry 82:709-715

Showing the most recent 10 out of 253 publications