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Quantitative Omics (QOC) Core

The goal of the Quantitative Omics Core (QOC) is to develop and apply innovative statistical, bioinformatics and data science methods to assist the research activities of Kansas Institute of Precision Medicine investigators. We offer help with:

  • study design
  • data management
  • data visualization
  • bioinformatics
  • access to high-performance computing
  • state-of-the-art bioinformatics software

We have experience in the analysis and interpretation of high-throughput ‘omic studies, including studies of gene expression (microarray and RNA-seq), pathway analysis, protein-DNA binding (e.g. ChIP-seq), DNA methylation, DNA variation and integrative multi-‘omic analysis.

Core Team

Our directors have extensive experience in the development and application of statistical methods for large-scale ‘omic data.

  • Devin Koestler, Ph.D., associate professor, Department of Biostatistics & Data Science
  • Jeffrey Thompson, Ph.D., assistant professor, Department of Biostatistics & Data Science

The core also includes:

  • Prabhakar Chalise, Ph.D., assistant professor, Department of Biostatistics & Data Science
  • bioinformatics specialists, Dong Pei, Ph.D., and Nanda Kumar, Ph.D.

This team has skills that span the domains of biostatistics, bioinformatics and statistical ‘omics. Together with access to high-performance computing and storage for large data sets, this core helps KIPM investigators with their study design, data collection, data management, analytics, bioinformatics and statistical needs.


For more information about the Omics core resources, contact