NIEHS Center for Environmental Health and Justice in Northern Manhattan

Study Design and Data Science Facility Core

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The goal of the Study Design and Data Science Facility Core is to respond to the growing need for using complex design and advanced computational methods and tools in environmental health sciences by providing a wide array of services to support the highly interdisciplinary research of the CEHJNM. The Data FC provides continued support with a unique array of data management, data analysis, and bioinformatics services, culminating in support for data interpretation, as well as results presentation and reporting. Investigators may elect to use all the services to fully support their studies or select only those needed to complement their expertise and research focus. For instance, basic scientists may greatly benefit from molecular/omic wet-lab services and bioinformatics, but may not be interested in specialized support for study design such as questionnaire design.  All services adhere to the NIH Rigor and Reproducibility Policy.

Visit the new NIEHS CEHJNM GitHub page, our Center Code Library for sharing and collaborating on coding projects. This resource helps streamline data management and analysis by allowing members to link project repositories and access existing code. Be sure to include a README with project details, data sources (with links if public), methods used, and any relevant publications.

CEHJNM GitHub

The Study Design and Data Science Facility Core (Data FC) provides intellectual and computational resources to plan, conduct, and analyze studies by continuing to support existing services, including:

  • Consultations on the design of observational, clinical, and experimental studies with an experienced epidemiologist;
  • Biostatistical consultations with one of three senior biostatisticians;
  • Data management.

The Core’s expanded expertise includes:

  • Statistical methods with genomics and epigenetics;

  • Multi-omics integration;

  • Training and guidance on handling and analyzing Geographical Information Systems (GIS) data;

  • Bayesian models;

  • Latent class methods;

  • Mixed effects models;

  • Clustering analyses;

  • Identifying, accessing, and analyzing the growing number of large data repositories in the public domain (“big” data).

The Core:

  • offers educational and training programs on the use of these methods;

  • assists with analysis and interpretation of data, and manuscript preparation;

  • fosters attention to the development of new methods/tools.

The unique combination of new and existing services in the Core will multiply opportunities and effectiveness in using the rich data that CEHNM members generate—as well as those already available in-house or in the public domain—to answer groundbreaking questions in environmental health research.Core members have expertise on all aspects of research planning, including study design; measurement of exposures, covariates, and outcomes; data management; spatial and temporal analysis; statistical power calculations; and statistical analysis.

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