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Center for Statistics in Biomedical Big Data (CSBBD)

Advancing statistical and computational methods to transform high-dimensional multi-modal biomedical data into actionable insights for precision health.

Biomedical Data Science Core

The Biomedical Data Science Core (BDSC) supports the Center for Molecular Studies in Digestive and Liver Diseases, led by Director Hongzhe Li, PhD, and Co-Director James Lewis, MD, MSCE. Offering fee-based services, the core provides Center investigators with study design consultation and implementation support. Key areas include data analysis, logistical planning, sample collection strategies, case report form templates, recruitment methods, and budget development.

Biomedical Data Science Core

BDSC Services

Basic Analyses

The Core will provide the following basic biostatistics and bioinformatics analysis for omics data with analyses performed by MS-level statisticians/bioinformaticians under the supervision of the Core PI. 

  • Basic statistical tests/regression analysis etc.
  • Data processing, quality control, batch-effects adjustments for high-throughput genomics, metagenomics, epigenomics, and metabolomics.
  • Exploratory analysis to identify clusters and patterns in the data sets using methods such as PCA, MDS, eSNE, etc.
  • Differential expression and differential abundance analysis based on omics data, including differential gene expression analysis based on RNA-seq data and differential abundance analysis based on shotgun metagenomics data.
  • Machine learning methods such as random forests to build predictive models for various  clinical outcomes using high dimensional omics data.
  • Support fully-collaborative grant-funded investigations. This includes preliminary data development, hypothesis formulation, grant narrative development, data analysis and biological inference, custom software development, and co-authored dissemination of findings. 

COST: This service involves one free meeting with Dr. Hongzhe Li and costs $150 per hour for staff analysis supervised by Dr. Li.

Customized Advanced Analyses

Penn Conference on Big Data

Penn Conference on Big Data

The Penn Conference on Big Data in Biomedical & Population Health Research unites experts to explore innovations in big data analytics, machine learning, and data-driven healthcare. Hosted by the DBEI, this annual event provides a collaborative forum for data scientists, biostatisticians, and industry leaders to share insights, tackle challenges, and advance applications in biomedicine and population health. Attendees gain essential skills to leverage big data for research advancements, improved patient outcomes, and the future of healthcare.