Faculty Profile

Maureen A. Sartor, PhD

Maureen A. Sartor, PhD

  • Associate Professor, Computational Medicine and Bioinformatics, Medical School
  • Associate Professor, Department of Biostatistics
  • 100 Washtenaw Ave.
  • 2017 Palmer Commons
  • Ann Arbor, Michigan 48109-2218

Maureen A. Sartor is an Associate Professor in the Department of Computational Medicine and Bioinformatics, with a joint appointment in Biostatistics. She received her PhD in Biostatistics in 2007 from the University of Cincinnati. Her research interests are in developing statistical and bioinformatics methods for analysis and interpretation of high throughput regulatory and epigenomics data. Her research focuses on cancer epigenomics, particularly oral squamous cell carcinomas. Early work focused on the analysis of microarray data. Recent work includes methods for analyzing ChIP-Seq data with replicates (PePr), functionally interpreting ChIP-seq results (ChIP-Enrich and Broad-Enrich), and testing for differentially methylated CpG sites from bisulfite sequencing data (methylSig). 

  • PhD, Biostatistics, University of Cincinnati, 2007
  • M.S., Biomathematics, North Carolina State University, 2000
  • B.S., Mathematics, minors in Biology and Computer science, Xavier University, 1998

  • Her research interests are in developing statistical and bioinformatics methods for analysis and interpretation of high throughput regulatory and epigenomics data. Her research focuses on cancer epigenomics, particularly oral squamous cell carcinomas. Early work focused on the analysis of microarray data. Recent work includes methods for analyzing ChIP-Seq data with replicates (PePr), functionally interpreting ChIP-seq results (ChIP-Enrich and Broad-Enrich), and testing for differentially methylated CpG sites from bisulfite sequencing data (methylSig). 

  • Cavalcante RG, Patil S, Park Y, Rozek LS, Sartor MA. Integrating DNA methylation and hydroxymethylation data with the mint pipeline. Cancer Res. 2017; 77(21):e27-e30.
  • Cavalcante RG, Sartor MA. annotatr: genomic regions in context. Bioinformatics. 2017; 33(15):2381-2383.
  • Cavalcante RG, Patil S, Weymouth TE, Bendiskas KG, Karnovsky A, Sartor MA. ConceptMetab: a tool for exploring relationships among biologically-related compound sets. Bioinformatics. 2016; 32(10):1536-43.
  • Lee C, Patil S, Sartor MA. RNA-Enrich: A cut-off free functional enrichment testing method for RNA-seq with improved detection power. Bioinformatics. 2015; 32(7):1100-2.
  • Agarwal S, Macfarlan TS, Sartor MA, Iwase S. Sequencing of first-strand cDNA library reveals full-length transcriptomes. Nat Commun. 2015; 6:6002.
  • Bai Y, Hassler J, Ziyar A, Li P, Wright Z, Menon R, Omenn GS, Cavalcoli JD, Kaufman RJ, Sartor MA. Novel bioinformatics method for identification of genome-wide non-canonical spliced regions using RNA-Seq data. PLoS One. 2014; 9(7):e100864.
  • Cavalcante R, Lee C, Patil S, Weymouth TE, Welch RP, Scott LJ, Sartor MA. Broad-Enrich: functional interpretation of large sets of broad genomic regions. Bioinformatics. (ECCB special issue) 2014; 30(17):i393-i400./li>
  • Zhang Y, Lin YH, Johnson TD, Rozek LS, Sartor MA. PePr: A peak-calling prioritization pipeline to identify consistent or differential peaks from replicated ChIP-Seq data. Bioinformatics. 2014; doi: 10.1093/bioinformatics/btu372.
  • Welch RP*, Lee C*, Imbriano PM, Patil S, Weymouth TE, Smith RA, Scott LJ, Sartor MA. ChIP-Enrich: Gene set enrichment testing for ChIP-seq data. NAR. 2014; doi:10.1093/nar/gku463 [Epub ahead of print].
  • Park Y, Figueroa ME, Rozek LS, Sartor MA. methylSig: a whole genome DNA methylation analysis pipeline. Bioinformatics. 2014; doi:10.1093/bioinformatics/btu339 [Epub ahead of print].

  • 2009-Present: Member, ISCB
  • 2011-Present: Member, AACR