PenNSAM Nutrition Analytic Core (PNAC)

The PenNSAM Nutrition Analytic Core (PNAC) provides services to analyze the big data sets generated from human diet and nutrition studies. PNAC utilizes advanced analytic techniques to analyze high dimensional datasets in genomics, metabolomics, proteomics and immune profiling. Advanced biostatistical, computational, and machine learning methods will be used to integrate results with clinical phenotyping information and to make correlations and predictions.


Services Offered

    1. Calculation of food pattern scores based on HDSR, DHQ, and ASA 24 data:
      *  The Healthy Eating Index-2015 (HEI-2015);
      *  The Alternative Mediterranean Diet (AMED);
      *  The Diet Inflammatory Index (DII);
      *  The Empirical Dietary Inflammatory Index (EDII);
      *   and The Diet Approach to Stop Hypertension (DASH) score
    2. Basic descriptive statistics, statistical tests and regression analysis,
      including generalized linear regression and Cox regression analysis.
    3. Data processing, quality control, batch-effects adjustments for metabolomics
      using the standard Bioinformatics software tools such as ComBat and SVA methods.
    4. Exploratory analysis to identify possible outliers, data transformation,
      clusters and patterns in the data sets using methods such as PCA, MDS, eSNE etc.
    5. Differential abundance analysis based on omics data including analysis
      on 16S rRNA gene and shotgun metagenomic microbiome data.
    6. Machine learning methods such as Lasso and random forests to build
      predictive models for various clinical outcomes using high dimensional omics data.

Service Fees for #1: $65 / hour
Contact Dr. Charlene Compher

Service Fees for #2-6: $150 / hour
Contact Dr. Hongzhe Li


Hongzhe Li, PhD


Perelman Professor of Biostatistics,
Epidemiology and Informatics
Professor of Biostatistics and Statistics
Vice Chair of Research Integration
Director, Center for Statistics in Big Data

Yun Li, PhD