PI: Michael I. Love


Assistant Professor
Department of Biostatistics
Department of Genetics
Member of Lineberger Comprehensive Cancer Center
University of North Carolina-Chapel Hill

@mikeloveGoogle ScholarBiostatistics Dept profile

michaelisaiahlove at gmail dot com *

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


  • May 2021 - Congratulations to Sean McCabe for winning the 2021 Larry Kupper Award for Best Dissertation Publication! Congratulations to Sarah Reifeis for being inducted into Delta Omega, and on receiving a Distinguished Student Paper Awards for ENAR 2021!
  • April 2021 - Wancen’s single cell allelic analysis package accepted into Bioconductor: airpart
  • April 2021 - Anqi and Nana’s MRLocus paper is published in PLOS Genetics: doi: 10.1371/journal.pgen.1009455
  • March 2021 - Arjun’s MOSTWAS paper is published in PLOS Genetics: doi: 10.1371/journal.pgen.1009398
  • January 2021 - Arjun’s DeCompress paper is published in Nucleic Acids Research: doi: 10.1093/nar/gkab031
  • January 2021 - Scott’s inferential summaries for scRNA-seq paper is published in Bioinformatics: doi: 10.1093/bioinformatics/btab001
  • November 2020 - Kwame won a poster award at ABRCMS 2020, and a JTech CSHL Biological Data Science 2020 Scholarship. His poster and abstract were for his R package: vizWithSCE.


The Love Lab uses statistical models to infer biologically meaningful patterns in high-dimensional datasets, and develops open-source statistical software for the Bioconductor Project. At UNC-Chapel Hill, we often collaborate with groups in the Genetics Department and the Lineberger Comprehensive Cancer Center, studying how genetic variants relevant to diseases are associated with changes in molecular and cellular phenotypes.

  • We collaborate with the Patro lab in the development of computational and statistical methods for quantification of RNA transcript abundance, including the software packages Salmon and tximeta.
  • We collaborate with the Stein lab in the study of genetic risk for neuropsychiatric disorders, leveraging data from molecular assays of chromatin accessibility and the transcriptome in neural progenitor cell lines to macroscale phenotypes such as gross human brain structure measured with MRI.
  • We collaborate with the Troester lab and the Carolina Breast Cancer Study, investigating the intersection between gene expression profiles of breast tumors and genetic risk for breast cancer, with a focus on racial disparities in patient outcomes.
  • We develop, support, and maintain the DESeq2 package for statistical analysis of RNA-seq and other sequencing experiments, and associated packages and workflows for analyzing genomics data. See the Software tab for more details.

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.

Past news items