Love Lab

Love Lab @ UNC-Chapel Hill

picture of the well on UNC campus, from unc.edu

Genetics Department ~ Biostatistics Department ~ UNC-Chapel Hill ~ see lab members for contact details.

News

  • September 2023 - Tidyomics preprint is posted: doi: 10.1101/2023.09.10.557072
  • August 2023 - Mike will give a workshop at BioC2023 on “Tidy genomic and transcriptomic single-cell analyses”
  • July 2023 - Mike starts as Associate Director of the Bioinformatics and Computational Biology (BCB) PhD program at UNC-Chapel Hill
  • July 2023 - Euphy’s paper on detecting allelic imbalance at the isoform-level is published:
    Euphy Y. Wu, Noor P. Singh, Kwangbom Choi, Mohsen Zakeri, Matthew Vincent, Gary A. Churchill, Cheryl L. Ackert-Bicknell, Rob Patro & Michael I. Love
    “SEESAW: detecting isoform-level allelic imbalance accounting for inferential uncertainty”
    doi: 10.1186/s13059-023-03003-x
  • April 2023 - Wancen’s bootRanges and Eric’s matchRanges methods published:
    Mu et al. “bootRanges: flexible generation of null sets of genomic ranges for hypothesis testing”
    doi: 10.1093/bioinformatics/btad190
    Davis et al. “matchRanges: generating null hypothesis genomic ranges via covariate-matched sampling”
    doi: 10.1093/bioinformatics/btad197
  • February 2023 - Ji-Eun’s preprint, Diffsig, a method for associating risk factors with mutational signatures:
    doi: 10.1101/2023.02.09.527740

Research

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 Won lab and the Mohlke lab as part of the IGVF consortium, studying the effect of disease-associated GWAS variants via in vivo massively parallel reporter assays (MPRA) to assess tissue-, sex-, and treatment-specific allelic effects.
  • 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. In collaboration with Stein lab researchers, we have developed the MRLocus method for identifying causal genes from QTL studies and GWAS.
  • 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.

Past news items

2022

2021

  • nullranges is released on Bioconductor! Joint work from Wancen and Eric Davis from Doug Phanstiel lab.
  • Wancen’s airpart method now has a preprint on bioRxiv: doi: 10.1101/2021.10.15.464546
  • 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!
  • Wancen’s single cell allelic analysis package accepted into Bioconductor: airpart
  • Anqi and Nana’s MRLocus paper is published in PLOS Genetics: doi: 10.1371/journal.pgen.1009455
  • Arjun’s MOSTWAS paper is published in PLOS Genetics: doi: 10.1371/journal.pgen.1009398
  • Arjun’s DeCompress paper is published in Nucleic Acids Research: doi: 10.1093/nar/gkab031
  • Scott’s inferential summaries for scRNA-seq paper is published in Bioinformatics: doi: 10.1093/bioinformatics/btab001

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.
  • Anqi’s last chapter is preprinted: “MRLocus: identifying causal genes mediating a trait through Bayesian estimation of allelic heterogeneity” doi: 10.1101/2020.08.14.250720
  • Arjun’s co-authored paper on NanoString normalization with Alina Hamilton is published in Briefings in Bioinformatics, doi: 10.1093/bib/bbaa163
  • Sarah Reifeis’s first paper is published in Genetic Epidemiology: “Assessing exposure effects on gene expression” doi: 10.1002/gepi.22324
  • Arjun Bhattacharya’s second and third papers are preprinted:
  • Tximeta is published in PLOS Computational Biology doi: 10.1371/journal.pcbi.1007664
  • Arjun Bhattacharya’s breast cancer TWAS is published in Genome Biology doi: 10.1186/s13059-020-1942-6
  • New paper on F1000Research: From first author Stuart Lee (Monash U.), “Fluent genomics with plyranges and tximeta” doi: 10.12688/f1000research.22259.1

2019

@mikelove@genomic.social