The Biostatistics Facility Core (BFC) provides statistical support for planned and ongoing research projects in environmental health sciences (EHS) by Center investigators, including pilot projects and projects related to Center initiatives. Specifically, BFC members: 1. Review research protocols from Center investigators who are requesting research grants or extramural support. In this capacity, members ofthe BFC assist in the development of study design, carry out sample size (power) calculations, and review proposed statistical methods. 2. Provide bioinformatics support to Center investigators. BFC personnel advise Center members on available technologies and bioinformatics resources, and advise on software tools for management and mining of data from gene expression, single nucleotide polymorphism (SNP), sequencing, methylation and other large-scale technologies. 3. Work closely with the IHSFC to provide support for the design and analysis of studies that utilize highvolume genetic approaches, geographical information system (GIS) technologies, and complex exposure assessment methods. 4. Provide an interface between Center investigators and statistical resources. The BFC matches statisticians to investigators so that, to the maximum extent possible. Center projects benefit from statisticians with particular expertise in the areas under investigation. 5. Stimulate collaboration between statisticians and other investigators by providing a focal point for statisticians to discuss issues with investigators from all four research cores. In particular, the BFC provides a natural link between the Study Design and Statistical Methodology Research Core (SDSMRC) and the other research cores. 6. Provide computer support for Center research projects. The BFC maintains a cluster computing system that is accessible to Center investigators. This system provides a central secure repository for storage and sharing of databases, and fast processors for executing computing intensive jobs. The BFC also assists Center investigators in their use of USC's High Performance Computing Cluster (HPCC), a large state-of the-art university-wide computing cluster.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Center Core Grants (P30)
Project #
5P30ES007048-20
Application #
8830364
Study Section
Environmental Health Sciences Review Committee (EHS)
Project Start
Project End
Budget Start
2015-04-01
Budget End
2016-03-31
Support Year
20
Fiscal Year
2015
Total Cost
$175,792
Indirect Cost
$67,279
Name
University of Southern California
Department
Type
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089
Chen, Wansu; Qian, Lei; Shi, Jiaxiao et al. (2018) Comparing performance between log-binomial and robust Poisson regression models for estimating risk ratios under model misspecification. BMC Med Res Methodol 18:63
Moss, Lilit C; Gauderman, William J; Lewinger, Juan Pablo et al. (2018) Using Bayes model averaging to leverage both gene main effects and G?×? E interactions to identify genomic regions in genome-wide association studies. Genet Epidemiol :
Lovett, Christopher; Cacciottolo, Mafalda; Shirmohammadi, Farimah et al. (2018) Diurnal variation in the proinflammatory activity of urban fine particulate matter (PM 2.5) by in vitro assays. F1000Res 7:596
Pomatto, Laura C D; Cline, Mayme; Woodward, Nicholas et al. (2018) Aging attenuates redox adaptive homeostasis and proteostasis in female mice exposed to traffic-derived nanoparticles ('vehicular smog'). Free Radic Biol Med 121:86-97
Alderete, Tanya L; Chen, Zhanghua; Toledo-Corral, Claudia M et al. (2018) Ambient and Traffic-Related Air Pollution Exposures as Novel Risk Factors for Metabolic Dysfunction and Type 2 Diabetes. Curr Epidemiol Rep 5:79-91
Reiner, Anne S; Sisti, Julia; John, Esther M et al. (2018) Breast Cancer Family History and Contralateral Breast Cancer Risk in Young Women: An Update From the Women's Environmental Cancer and Radiation Epidemiology Study. J Clin Oncol 36:1513-1520
Laville, Vincent; Bentley, Amy R; Privé, Florian et al. (2018) VarExp: estimating variance explained by genome-wide GxE summary statistics. Bioinformatics 34:3412-3414
Kalkbrenner, Amy E; Windham, Gayle C; Zheng, Cheng et al. (2018) Air Toxics in Relation to Autism Diagnosis, Phenotype, and Severity in a U.S. Family-Based Study. Environ Health Perspect 126:037004
Stram, Douglas A; Jiang, Xuejuan; Varma, Rohit et al. (2018) Factors Associated with Prevalent Diabetic Retinopathy in Chinese Americans: The Chinese American Eye Study. Ophthalmol Retina 2:96-105
Dong, Jing; Levine, David M; Buas, Matthew F et al. (2018) Interactions Between Genetic Variants and Environmental Factors Affect Risk of Esophageal Adenocarcinoma and Barrett's Esophagus. Clin Gastroenterol Hepatol 16:1598-1606.e4

Showing the most recent 10 out of 653 publications