Data Science Core Overview

The Data Science Core (DSC) has assembled a team of data scientists, genome biologists and biostatisticians to: 1) work with researchers throughout the state of Kansas in designing experiments, analyzing data, and interpreting results that lead to publications and grant applications; 2) provide access to computational resources to facilitate the analysis of large data sets; 3) develop and help implement analysis pipelines to foster reproducible research practices; 4) provide training opportunities in the form of direct mentorship, workshops, and seminars for faculty and their trainees; 5) generate publication-ready figures and other products necessary for publications and grant proposals; and 6) consult on the development of course materials to help faculty train the next generation of bioscientists.

How to Contact Us

We are available to assist researchers across the state of Kansas in the design and implementation of rigorous and powerful experiments using genomics and related approaches. These collaborations work best when we are able to contribute to the design of experiments, and so we encourage you to contact us at the earliest stages of planning. Please reach out to us using this form and we will schedule a consultation about your analysis and/or training needs.

University of Kansas (KU-L)

The Data Science Core at KU-Lawrence is led by Dr. Stuart Macdonald (Professor, Molecular Biosciences). Dr. Macdonald’s research interest is in understanding the molecular genetic basis of complex traits, and his group uses an array of genomic and analytical tools to accomplish this. The KU-L DSC is staffed by a full-time genomic data scientist, Dr. Brian Sanderson (see below), who has an array of experience with the computational analysis of genomics data. Our website describes our facility and services. We are able to assist with a range of data analysis problems, including (but not limited to):

• Using RNA-sequencing to understand changes in gene expression among individuals, tissues, and treatments.
• Understanding the relationship between genetic and phenotypic variation.
• Finding variants in whole-genome re-sequencing data.

We are available to assist in the design of rigorous/powerful genomics experiments. We will implement efficient, reproducible workflows for analyzing genomics data. We can generate publication-ready figures, and other products necessary for publications and grant proposals. And we can provide education and training in the analysis of next-generating sequencing data (e.g., from whole genome sequencing, RNAseq, etc) to answer biological questions.

University of Kansas Medical Center (KUMC)

The KUMC DSC is led by Dr. Prabhakar Chalise, Associate Professor, and Dr. Devin Koestler, Professor, both in the Department of Biostatistics & Data Science at the University of Kansas Medical Center. Dr. Chalise's primary research interest is in utilizing his training in biostatistics and quantitative sciences to understand the biology of living systems. He works closely in the studies of molecular basis of the disease using various types of genetics and genomics data. Most of such datasets are high dimensional in nature which include SNP, mRNA expression, microRNA, DNA methylation, and protein expression. Dr. Koestler’s specialty is statistical genomics. He focuses on the development and application of novel bioinformatics/statistical methodologies for identifying biologically and clinically relevant patterns in high-throughput ‘omic data, with an emphasis on computationally efficient clustering methodologies for identifying molecular subtypes of human diseases. Bioinformatics specialists at the KUMC Core have extensive experience in the design and analysis of ‘omic studies using both microarray and high-throughput sequencing technologies and provide the core with expertise in statistical analysis and clinical studies.

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Data Science Core Contacts

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UNIVERSITY OF KANSAS

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UNIVERSITY OF KANSAS MEDICAL CENTER

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