Research in the Sartor Lab interfaces with high-throughput statistical analysis and bioinformatics methods to interpret data with respect to biological knowledge.  The laboratory focuses on developing methods and tools for analysis of genomic and epigenomic data.  Previously, her research has focused on the analysis of microarray data. Her current work involves developing methods for ChIP-Seq data to better assess the biological functionality of results, methods for genome-wide DNA methylation analysis, and methods for integration with other data types. Her lab also develops methods and tools for functional or gene set enrichment testing and is involved in the development of concept mapping software.

Gene set enrichment testing methods

Gene set enrichment testing methods are in wide-spread use for interpreting the results of high-throughput gene expression experiments, and assist investigators to bridge the gap from studying lists of genes to understanding the biological pathways and processes at a systems level perspective . We’ve developed multiple methods and tools for this analysis:  ConceptGen and LRpath. More recently, such tests have been adopted in the analysis of experiments assessing genome-wide binding or differential binding of transcription factors, histone modifications, and DNA methylation.  However, use of the standard Fisher’s Exact test with such data can lead to unacceptably biased results. We’ve developed a novel gene set enrichment testing method, ChIP-Enrich, designed specifically for ChIP-Seq type data that corrects for multiple biases inherent in the testing process.  We are also developing methods and tools for enrichment testing of metabolomics and proteomics data sets.

Analysis of ChIP-Seq data with replicates

Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is now the standard to identify in vivo protein-DNA interaction or histone modification sites on a genome-wide scale. While most ChIP-Seq peak calling programs report the statistical significance of how likely a region is bound by the protein of interest, little effort is devoted to assessing biological variance or prioritizing the peaks based on the binding profile relative to external annotations.  Biological variation is extremely important when performing differential analyses, such as comparing histone modification profiles between groups of individuals.  We’ve developed a Peak-finding and Prioritization (PePr) pipeline that accounts for variation among biological samples and optionally takes into account location of peaks relative to gene structure information.  We are working to further expand our pipeline to include additional sources of annotation and prior data and improve background variance modeling.

Head and Neck squamous cell carcinomas (HNSCC)

Our lab’s main biological focus is cancer, concentrating on HNSCC, and in particular oropharyngeal cancers.  Oropharyngeal cancers are interesting due to the fact that significant numbers are caused by use of tobacco products, however a substantial percent are also caused by oncogenic human papillomavirus (HPV).  Thus, the oropharynx provides a tumor site in which one is able to study molecular differences between chemical-induced and viral-induced tumors. We are currently studying the molecular signatures (genetic, genomic, and epigenomic) between HPV-positive and HPV-negative oropharyngeal and oral cavity tumors, with the goal of identifying novel biomarkers for prognosis and/or treatment.


Epigenetics is defined as the study of heritable traits due to a mechanism other than the DNA itself.  Epigenetics studies marks such as DNA methylation and modifications to histone tails. Over the past few years, the field of epigenomics has been revolutionized by a myriad of new high-throughput approaches to assess genome-wide epigenetic marks.  These technologies have led to several exciting discoveries of aberrant epigenetic marks in diseases such as cancers, where important epigenetic events often occur early in the carcinogenic process.  We are comparing and contrasting DNA methylation across many types of cancer, and studying histone modifications in a select set of cancer cell lines. Our lab is developing a method, MethylSig, for testing for differential methylated regions for whole-genome or reduced representation bisulfite sequencing experiments. A long term goal is to be able to identify which epigenetic changes “drive” the progression of cancer.  In addition to cancer, exposure to environmental chemicals is also able to modify the epigenome, and several are associated with increased risk of disease later in life.  In collaboration with the Dolinoy Lab, we are studying the effects of early-life exposure to Bisphenol A (BPA) on the epigenome.