Love Lab

Papers

Publications and preprints

Note: For a full list of publications, see this Google Scholar page, or the PI's CV under Lab members. The following partial list includes papers and preprints either led by members of the lab, co-supervised work, or work with relevant software contributions from members of the lab.

Wancen Mu, Eric S. Davis, Kathleen Reed, Douglas Phanstiel, Michael I. Love, Didong Li. Gaussian Processes for Time Series with Lead-Lag Effects with applications to biology data. arXiv, January 2024. doi: 10.48550/arXiv.2401.07400

William J Hutchison, Timothy J Keyes, Helena L Crowell, Charlotte Soneson, Wancen Mu, Ji-Eun Park, Eric S Davis, Abdullah A Nahid, Ming Tang, Victor Yuan, Pierre-Paul Axisa, Jonathan W Kitt, Chi-Lam Poon, Noriaki Sato, Raphael Gottardo, Martin Morgan, Stuart Lee, Michael Lawrence, Stephanie C Hicks, Garry P Nolan, Kara L Davis, Anthony T Papenfuss, Michael I Love, Stefano Mangiola. The tidyomics ecosystem: Enhancing omic data analyses. bioRxiv, September 2023. doi: 10.1101/2023.09.10.557072

Euphy 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. Genome Biology, July 2023. doi: 10.1186/s13059-023-03003-x

  • SEESAW in fishpond R/Bioconductor package

Noor Pratap Singh, Michael I. Love, and Rob Patro. TreeTerminus —creating transcript trees using inferential replicate counts. iScience, June 2023. doi: 10.1016/j.isci.2023.106961

Wancen Mu, Eric Davis, Stuart Lee, Mikhail Dozmorov, Douglas H. Phanstiel, Michael I. Love. bootRanges: Flexible generation of null sets of genomic ranges for hypothesis testing. Bioinformatics, April 2023. doi: 10.1093/bioinformatics/btad190

Eric S. Davis, Wancen Mu, Stuart Lee, Mikhail G. Dozmorov, Michael I. Love, Douglas H. Phanstiel. matchRanges: Generating null hypothesis genomic ranges via covariate-matched sampling. Bioinformatics, April 2023. doi: 10.1093/bioinformatics/btad197

  • matchRanges in nullranges R/Bioconductor package

Ji-Eun Park, Markia A. Smith, Sarah C. Van Alsten, Andrea Walens, Di Wu, Katherine A. Hoadley, Melissa A. Troester, Michael I. Love. Diffsig: Associating Risk Factors With Mutational Signatures. bioRxiv, February 2023. doi: 10.1101/2023.02.09.527740

Sarah A. Reifeis, Michael G. Hudgens, Melissa A. Troester, Michael I. Love. Assessing Etiologic Heterogeneity for Multinomial Outcome with Two-Phase Outcome-Dependent Sampling Design. medRxiv July 2022. doi: 10.1101/2022.07.20.22277805

Wancen Mu, Hirak Sarkar, Avi Srivastava, Kwangbom Choi, Rob Patro, Michael I. Love. Airpart: Interpretable statistical models for analyzing allelic imbalance in single-cell datasets. Bioinformatics, April 2022. doi: 10.1093/bioinformatics/btac212,

Achal Patel, Montserrat García-Closas, Andrew F. Olshan, Charles M. Perou, Melissa A. Troester, Michael I. Love, Arjun Bhattacharya. Gene-Level Germline Contributions to Clinical Risk of Recurrence Scores in Black and White Patients with Breast Cancer. Cancer Research, January 2022. doi: 10.1158/0008-5472.CAN-21-1207

Sean D. McCabe, Andrew B. Nobel, Michael I. Love. ACTOR: a latent Dirichlet model to compare expressed isoform proportions to a reference panel. Biostatistics, May 2021. doi: 10.1093/biostatistics/kxab013,

Anqi Zhu (1), Nana Matoba (1), Emmaleigh Wilson, Amanda L. Tapia, Yun Li, Joseph G. Ibrahim, Jason L. Stein, Michael I. Love. MRLocus: identifying causal genes mediating a trait through Bayesian estimation of allelic heterogeneity. PLOS Genetics, April 2021. doi: 10.1371/journal.pgen.1009455,

Arjun Bhattacharya, Yun Li, Michael I. Love. Multi-omic strategies for transcriptome-wide prediction and association studies. PLOS Genetics, March 2021. doi: 10.1371/journal.pgen.1009398,

Arjun Bhattacharya, Alina M. Hamilton, Melissa A. Troester, Michael I. Love. DeCompress: tissue compartment deconvolution of targeted mRNA expression panels using compressed sensing. Nucleic Acids Research, January 2021. doi: 10.1093/nar/gkab031,

Scott Van Buren, Hirak Sarkar, Avi Srivastava, Naim U. Rashid, Rob Patro, Michael I. Love. Compression of quantification uncertainty for scRNA-seq counts. Bioinformatics, January 2021. doi: 10.1093/bioinformatics/btab001,

  • makeInfReps in fishpond R/Bioconductor package

Joshua P. Zitovsky, Michael I. Love. Fast effect size shrinkage software for beta-binomial models of allelic imbalance. F1000Research, December 2020. doi: 10.12688/f1000research.20916.2,

  • method="betabinCR" in apeglm R/Bioconductor package

Nana Matoba, Michael I. Love, Jason L. Stein. Evaluating brain structure traits as endophenotypes using polygenicity and discoverability. Human Brain Mapping, October, 2020. doi: 10.1002/hbm.25257

Arjun Bhattacharya (1), Alina M. Hamilton (1), Helena Furberg, Eugene Pietzak, Mark P. Purdue, Melissa A. Troester, Katherine A. Hoadley (N), Michael I. Love (N). An approach for normalization and quality control for NanoString RNA expression data. Briefings in Bioinformatics, August 2020. doi: 10.1093/bib/bbaa163, PMC8138885

Hirak Sarkar, Avi Srivastava, Hector Corrada Bravo, Michael I. Love, Rob Patro. Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data. Bioinformatics, July 2020. doi: 10.1093/bioinformatics/btaa448,

Sarah A. Reifeis, Michael G. Hudgens, Mete Civelek, Karen L. Mohlke, Michael I. Love. Assessing exposure effects on gene expression. Genetic Epidemiology, June, 2020. doi: 10.1002/gepi.22324, PMC7429346

Charlotte Soneson, Federico Marini, Florian Geier, Michael I. Love, Michael B. Stadler. ExploreModelMatrix: Interactive exploration for improved understanding of design matrices and linear models in R. F1000Research, June 2020. doi: 10.12688/f1000research.24187.1,

Michael I. Love, Charlotte Soneson, Peter F. Hickey, Lisa K. Johnson, N. Tessa Pierce, Lori Shepherd, Martin Morgan, Rob Patro. Tximeta: Reference sequence checksums for provenance identification in RNA-seq. PLOS Computational Biology, February 2020. doi: 10.1371/journal.pcbi.1007664,

Arjun Bhattacharya, Montserrat Garcia-Closas, Andrew F. Olshan, Charles M. Perou, Melissa A. Troester, Michael I. Love. A framework for transcriptome-wide association studies in breast cancer in diverse study populations. Genome Biology, February 2020. doi: 10.1186/s13059-020-1942-6

Stuart Lee, Michael Lawrence, Michael I. Love. Fluent genomics with plyranges and tximeta. F1000Research, February 2020. doi: 10.12688/f1000research.22259.1,

Anqi Zhu, Avi Srivastava, Joseph G. Ibrahim, Rob Patro, Michael I. Love. Nonparametric expression analysis using inferential replicate counts. Nucleic Acids Research, August 2019. doi: 10.1093/nar/gkz622, swish supplement PDF,

  • swish function in fishpond R/Bioconductor package

Sean D. McCabe, Dan-Yu Lin, Michael I. Love. Consistency and overfitting of multi-omics methods on experimental data. Briefings in Bioinformatics, July 2019. doi: 10.1093/bib/bbz070, PMC7373174,

(Review) Koen Van Den Berge, Katharina Hembach, Charlotte Soneson, Simone Tiberi, Lieven Clement, Michael I. Love, Rob Patro, Mark Robinson. RNA sequencing data: hitchhiker’s guide to expression analysis. Annual Review of Biomedical Data Science, April 2019. doi: 10.1146/annurev-biodatasci-072018-021255, https://peerj.com/manuscripts/33040/ (Review)

Anqi Zhu, Joseph G. Ibrahim, Michael I. Love. Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences. Bioinformatics, November 2018. doi: 10.1093/bioinformatics/bty895,

  • apeglm R/Bioconductor package

Michael I. Love, Charlotte Soneson, and Rob Patro. Swimming downstream: statistical analysis of differential transcript usage following Salmon quantification. F1000Research, October 2018. doi: 10.12688/f1000research.15398.3

Koen Van den Berge (1), Fanny Perraudeau (1), Charlotte Soneson, Michael I. Love, Davide Risso, Jean-Philippe Vert, Mark D. Robinson, Sandrine Dudoit (N), Lieven Clement (N). Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications. Genome Biology, February 2018. doi: 10.1186/s13059-018-1406-4,

Rob Patro, Geet Duggal, Michael I. Love, Rafael A. Irizarry, Carl Kingsford. Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods, March 2017. PMC, doi: 10.1038/nmeth.4197, CMU PR,

Michael I. Love, Matthew Huska, Marcel Jurk, Robert Schöpflin, Stephan Starick, Kevin Schwahn, Samantha Cooper, Keith Yamamoto, Morgane Thomas-Chollier, Martin Vingron, Sebastiaan Meijsing. Role of the chromatin landscape and sequence in determining cell type-specific genomic glucocorticoid receptor binding and gene regulation. Nucleic Acids Research, November 2016. doi: 10.1093/nar/gkw1163

Pre- publications:

Michael I. Love, John B. Hogenesch, Rafael A. Irizarry. Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation. Nature Biotechnology, September 2016. PMC, doi: 10.1038/nbt.3682, blog post, YouTube,

  • alpine R/Bioconductor package

Charlotte Soneson, Michael I. Love, Mark D. Robinson. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Research, December 2015. PMC, doi: 10.12688/f1000research.7563.1,

Michael I. Love, Simon Anders, Vladislav Kim, Wolfgang Huber. RNA-seq workflow: gene-level exploratory analysis and differential expression. F1000Research, October 2015. PMC, doi: 10.12688/f1000research.7035.1,

Wolfgang Huber, Vincent J. Carey, Robert Gentleman, Simon Anders, Marc Carlson, Benilton S. Carvalho, Hector Corrada C. Bravo, Sean Davis, Laurent Gatto, Thomas Girke, Raphael Gottardo, Florian Hahne, Kasper D. Hansen, Rafael A. Irizarry, Michael Lawrence, Michael I. Love, James MacDonald, Valerie Obenchain, Andrzej K. Oleś, Hervé Pagès, Alejandro Reyes, Paul Shannon, Gordon K. Smyth, Dan Tenenbaum, Levi Waldron, Martin Morgan. Orchestrating high-throughput genomic analysis with Bioconductor. Nature Methods, February 2015. PMC, doi: 10.1038/nmeth.3252

Michael I. Love, Wolfgang Huber, Simon Anders. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, December 2014. PMC, doi: 10.1186/s13059-014-0550-8,

  • DESeq2 R/Bioconductor package

Michael I. Love, Alena Myšičková, Ruping Sun, Vera Kalscheuer, Martin Vingron, Stefan A. Haas. Modeling read counts for CNV detection in exome sequencing data. Statistical Applications in Genetics and Molecular Biology, January 2011. PMC, doi: 10.2202/1544-6115.1732,