PI: Michael I. Love
Assistant Professor
Department of Biostatistics
Department of Genetics
Member of Lineberger Comprehensive Cancer Center
University of North Carolina-Chapel Hill

Google Scholar
Biostatistics Dept. bio

michaelisaiahlove at gmail dot com *

* for software questions, do not email, instead use the Bioconductor support site



  • April 2018 - Anqi Zhu sent off the first preprint from the lab: Heavy-tailed prior distributions for sequence count data, which describes the apeglm software.
  • February 2018 - Michael Love gave a talk at UVA’s Center for Public Health Genomics: Fragment-level bias modeling for RNA-seq Data Analysis (link to Google Slides).
  • December 2017 - Anqi Zhu and Michael Love featured in a Nature article talking about the Bioconductor Project for genomic data analysis.
  • December 2016 - Michael Love gave a talk at UMD’s Computational Biology, Bioinformatics & Genomics seminar series.
  • October 2016 - Michael Love gave a talk at the Triangle Statistical Genetics Meeting, SAS Campus, Cary.


The Love Lab uses statistical models to infer biologically meaningful patterns from high-throughput sequencing data, and develops open-source statistical software for the Bioconductor Project. A major effort of the lab is maintaining the DESeq2 package for statistical analysis of RNA-seq experiments, and associated packages and workflows for analyzing genomics data.

PI - Background

From 2013-2016, I was a Postdoctoral Fellow in the group of Rafael Irizarry in the Biostatistics and Computational Biology Department at the Dana-Farber Cancer Institute and the Harvard TH Chan School of Public Health. I completed a PhD in Computational Biology and Scientific Computing (2013) in the Vingron Department at the Max Planck Institute for Molecular Genetics in Berlin and the Mathematics and Informatics Department of the Freie Universität, Berlin. I completed a Statistics M.S. (2010) and Mathematics B.S. (2005) at Stanford University.