Data Analytics Core

Overview of Services

The Data Analytics Core (DAC) is the umbrella core for independent yet complementary data science, biostatistics, and bioinformatics core facilities currently operating in the School of Medicine. The goal of the DAC is to provide an end-to-end standardization of all core operational functions, from initial engagement to project commencement to project completion.


Collectively, the cores comprising the DAC offer investigators a full menu of data science related services, including experimental design (e.g. population health, epidemiology, clinical, and basic science), experimental execution (e.g. functional genomics), survey methodologies, statistical analyses, NGS technologies, clinical informatics, data/study management and compliance (i.e. SHED), and the utilization of existing and creation of new computational resources.


CFAR Users should engage the Biostatistics Core led by Sara Debanne



Bioinformatics Core:
Provide specialized bioinformatics services in genomics, proteomics, systems biology. Extensive list of pipelines and approaches to address all needs for large -omics analysis, reporting, and visualization.


Gurkan Bebek, PhD
Assistant Professor


Jean-Eudes (Johnny) Dazard, PhD
Assistant Professor


Biostatistics Core:
Provides expertise for the design of clinical, translational, meta-analytic, and observational epidemiologic studies, including complex sample size calculations. We have expertise in analytic approaches, and their interpretation, for various data types, including cross-sectional, correlated, and longitudinal data. Core members have extensive experience in methodological research as applied to both infectious and chronic diseases.


Sara Debanne, PhD


Case Comprehensive Cancer Center Biostatistics and Bioinformatics Shared Resource:
Provides comprehensive biostatistical supports: it links biostatistics, bioinformatics, informatics, clinical trials, epidemiology, and statistical computing to support proposal/clinical protocol development, pilot studies, funded grants and to provide data analysis services including big and dense omics datasets.


Ming Li
Associate Professor


Clinical Research Design and Analysis Core:
Clinical study design and analysis. Biostatistical analysis of clinical trials, retrospective studies and cohort studies, including multivariable analyses. Analysis of genetic data.  


Cheryl Thompson, PhD
Assistant Professor


Computational Biology Core:
Provide computational and analytical support for large dataset analysis specializing in next-generation sequencing data. Supports massive data sets with standardized and custom pipelines for data processing and analysis of RNA-seq, DNA-seq, microbiome, and other genomics experiments such as ATAC-Seq, ChIP-Seq, RIP-Seq and ribosome profiling. We can provide various analysis approaches for extracting new biological insights. We are happy to assist you from step one, which includes working closely with sequencing cores at CWRU and Cleveland Clinic.


E. Ricky Chan, PhD
Research Scientist


CTSC Research Resources Core:
Offers a range of services in the areas of data management, research design, DSMBs, regulatory requirements, clinical research education, and plan for data transfer to/from an outside entity. 


Carolyn Apperson
Sr. Research Associate


Offers a range of services to conduct outcomes/effectiveness research, and disparities research using population-based databases. Databases include vital records, Medicare and Medicaid enrollment and claims, Ohio Cancer Incidence Surveillance System, Healthcare Cost and Utilization Project, survey, and U.S. census data.


Siran Koroukian, PhD
Associate Professor



Leadership Personnel

Sudha Iyengar Professor Director of the DAC                                      
Sara Debanne Professor Co-Director of the DAC/Director of the Biostatistics Core
Ming Li Associate Professor Director CCCC Biostatistics and Bioinformatics Core
Paul Poelson  Associate Statff Co-Director CCCC Biostatistics and Bioinformatics Core

Links and Resources

  1. Data Analytics Core
  2. Biostatistics & Bioinformatics