Genomics Analysis Core

Our Services

Welcome to the Genomics Analysis Core (GAC)


The Genomics Analysis Core (GAC) provides bioinformatics analysis for data from all genomics platforms including microarrays and next generation sequencing applications. The GAC provides support for all aspects of translational studies – from experimental design to data analysis to publication.  The GAC works closely with the Health Science Library System Mol Bio Service (HSLS – Mol Bio), the Center for Research Computing, in directing researchers appropriate resource for genomics education, analysis and computing.


Bioinformatic Data Analysis

The GAC provides bioinformatics support for RNA Seq, Exome Seq, Whole Genome Seq, ChiP Seq, ATAC Seq and other emerging genomic applications.

High Throughput Computing

The GAC works with the Center for Research Computing (CRC) and the Pittsburgh Supercomputing Center (PSC) in development and implementation of bioinformatic pipelines and High Performance Computing (HPC) resources.

Examples of projects the GAC has undertaken:

  • De novo transcriptomics using Illumina RNA Seq data to understand the molecular basis for differences in salamander and lizard tail regeneration.
  • Illumina RNA Seq data from developing male and female hypothalamus and cortex to examine sex differences in glucocorticoid and statin regulation in these brain regions.
  • Ion Torrent whole exome data from pediatric patients with sepsis to identify variants that may be associated with specific clinical phenotypes.
  • A custom pipeline for analysis of Illumina NGS and Sanger sequencing data was developed to detect low frequency HIV RT variants in clinical trial samples.
  • Cells infected with wild type HSV and with early gene mutant HSV is to understand the time course of cellular and viral transcriptional changes. This is an integrative analysis using both RNA Seq for transcriptomics and ChIP Seq for PolII chromatin binding sites.
  • Transcriptomic changes after administration of inactivated and live attenuated influenza vaccine to pediatric patients to understand correlation between immune regulatory molecules and vaccine efficacy.

Contact & Scheduling

Uma Chandran, PhD, MSIS
Director, Genomics Analysis Services
Research Associate Professor, Department of Biomedical Informatics
Phone: 412-648-9326
For more information, please go to <Contact Us>

University of Pittsburgh Department of Biomedical Informatics (DBMI) Faculty with bioinformatics research interests:

Madhavi Ganapathiraju, PhD (Protein-Protein Interactions and Computational and Systems Biology)

Xia Jiang, PhD (Breast Cancer Genomics, GWAS, Multi-Genics)

Songjian Lu, PhD (Cancer Genomics, Graph Theory)

Xinghua Lu, PhD (Cancer Genomics, Knowledge Representation)

Gregory Cooper, PhD (Casual Modeling and Discovery)

Erik S. Wright (antibioitic resistance)