Regulatory network topology and the genetic architecture of gene expression
Matthew Aguirre, Jeffrey P Spence, Guy Sella, Jonathan K. Pritchard, "Gene regulatory network structure informs the distribution of perturbation effects."; bioRxiv, 2025.
CV
Education
- Ph.D in Biomedical Informatics, Stanford University, 2025.
- M.S. in Statistics, Stanford University, 2023.
- B.A. in Applied Mathematics, cum laude, Harvard University, 2017.
Work experience
Fall 2025-Present: Postdoctoral Fellow at Genentech, with Mark McCarthy and Aviv Regev.
- Fall 2019-Spring 2025: Ph.D student in Biomedical Informatics with Jonathan Pritchard, at Stanford University
- Thesis: Modeling genetic and experimental perturbations to gene regulatory networks.
- Summer 2023: Bioinformatics Intern at Guardant Health. Performed application development for the INFINITY platform.
- Fall 2017-Summer 2019: Research data analyst with Manuel Rivas and James Priest, at Stanford University
- Conducted large-scale studies in genetic epidemiology and contributed to the Global Biobank Engine.
- Summer 2015-Spring 2017: Undergraduate researcher in the MacArthur Lab and Data Science Platform, at the Broad Institute of Harvard and MIT
- Contributed to data quality control for the gnomAD project
Awards
- Teaching Award, Stanford Department of Biomedical Data Science (2022)
- PhD Fellowship, Microsoft Research (2021)
- Reviewers’ choice abstract, American Society of Human Genetics (ASHG) Annual Meeting (2020)
Publications
Gene regulatory network structure informs the distribution of perturbation effects
Matthew Aguirre, Jeffrey P Spence, Guy Sella, Jonathan K. Pritchard, "Gene regulatory network structure informs the distribution of perturbation effects." bioRxiv, 2024.
Learning epistatic polygenic phenotypes with Boolean interactions
Merle Behr, Karl Kumbier, Aldo Cordova-Palomera, Matthew Aguirre, Omer Ronen, Chengzhong Ye, Euan Ashley, Atul J Butte, Rima Arnaout, Ben Brown, James Priest, Bin Yu, "Learning epistatic polygenic phenotypes with Boolean interactions." PLoS ONE, 2024.
Transcriptomics and chromatin accessibility in multiple African population samples
Marianne K DeGorter, Pagé C Goddard, Emre Karakoc, Soumya Kundu, Stephanie M Yan, Daniel Nachun, Nathan Abell, Matthew Aguirre, Tommy Carstensen, Ziwei Chen, Matthew Durrant, Vikranth R Dwaracherla, Karen Feng, Michael J Gloudemans, Naiomi Hunter, Mohana PS Moorthy, Cristina Pomilla, Kameron B Rodrigues, Courtney J Smith, Kevin S Smith, Rachel A Ungar, Brunilda Balliu, Jacques Fellay, Paul Flicek, Paul J McLaren, Brenna Henn, Rajiv C McCoy, Lauren Sugden, Anshul Kundaje, Manjinder S Sandhu, Deepti Gurdasani, Stephen B Montgomery, "Transcriptomics and chromatin accessibility in multiple African population samples." bioRxiv, 2023.
Oligogenic Architecture of Rare Noncoding Variants Distinguishes 4 Congenital Heart Disease Phenotypes
Mengyao Yu, Matthew Aguirre, Meiwen Jia, Ketrin Gjoni, Aldo Cordova-Palomera, Chad Munger, Dulguun Amgalan, X Rosa Ma, Alexandre Pereira, Catherine Tcheandjieu, Christine Seidman, Jonathan Seidman, Martin Tristani-Firouzi, Wendy Chung, Elizabeth Goldmuntz, Deepak Srivastava, Ruth JF Loos, Nathalie Chami, Heather Cordell, Martina Dreßen, Bertram Mueller-Myhsok, Harald Lahm, Markus Krane, Katherine S Pollard, Jesse M Engreitz, Sarah A Gagliano Taliun, Bruce D Gelb, James R Priest, "Oligogenic Architecture of Rare Noncoding Variants Distinguishes 4 Congenital Heart Disease Phenotypes" Circulation: Genomic and Precision Medicine, 2023.
Genetic Determinants of the Interventricular Septum Are Linked to Ventricular Septal Defects and Hypertrophic Cardiomyopathy
Mengyao Yu, Andrew R Harper, Matthew Aguirre, Maureen Pittman, Catherine Tcheandjieu, Dulguun Amgalan, Christopher Grace, Anuj Goel, Martin Farrall, Ke Xiao, Jesse Engreitz, Katherine S Pollard, Hugh Watkins, James R Priest, "Genetic Determinants of the Interventricular Septum Are Linked to Ventricular Septal Defects and Hypertrophic Cardiomyopathy" Circulation: Genomic and Precision Medicine, 2023.
Integration of rare expression outlier-associated variants improves polygenic risk prediction
Craig Smail, Nicole Ferraro, Qin Hui, Matthew Durrant, Matthew Aguirre, Yosuke Tanigawa, Marissa Keever-Keigher, Abhiram Rao, Johanne Justesen, Xin Li, Michael Gloudemans, Themistocles Assimes, Charles Kooperberg, Alexander Reiner, Jie Huang, Christopher O'Donnell, Yan Sun, Manuel Rivas, Stephen Montgomery, "Integration of rare expression outlier-associated variants improves polygenic risk prediction." The American Journal of Human Genetics, 2022.
Bayesian model comparison for rare-variant association studies
Guhan Venkataraman, Christopher DeBoever, Yosuke Tanigawa, Matthew Aguirre, Alexander Ioannidis, Hakhamanesh Mostafavi, Chris Spencer, Timothy Poterba, Carlos Bustamante, Mark Daly, Matti Pirinen, Manuel Rivas, "Bayesian model comparison for rare-variant association studies." The American Journal of Human Genetics, 2021.
Polygenic risk modeling with latent trait-related genetic components
Matthew Aguirre, Yosuke Tanigawa, Guhan Venkataraman, Rob Tibshirani, Trevor Hastie, Manuel Rivas, "Polygenic risk modeling with latent trait-related genetic components." European Journal of Human Genetics, 2021.
Genetics of 35 blood and urine biomarkers in the UK Biobank
Nasa Sinnott-Armstrong, Yosuke Tanigawa, David Amar, Nina Mars, Christian Benner, Matthew Aguirre, Guhan Venkataraman, Michael Wainberg, Hanna Ollila, Tuomo Kiiskinen, et. al., "Genetics of 35 blood and urine biomarkers in the UK Biobank." Nature Genetics, 2021.
A phenome-wide association study of 26 mendelian genes reveals phenotypic expressivity of common and rare variants within the general population
Catherine Tcheandjieu, Matthew Aguirre, Stefan Gustafsson, Priyanka Saha, Praneetha Potiny, Melissa Haendel, Erik Ingelsson, Manuel Rivas, James Priest, "A phenome-wide association study of 26 mendelian genes reveals phenotypic expressivity of common and rare variants within the general population." PLoS genetics, 2020.
A deep learning classifier for local ancestry inference
Matthew Aguirre, Jan Sokol, Guhan Venkataraman, Alexander Ioannidis, "A deep learning classifier for local ancestry inference." arXiv preprint arXiv:2011.02081, 2020.
A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank
Junyang Qian, Yosuke Tanigawa, Wenfei Du, Matthew Aguirre, Chris Chang, Robert Tibshirani, Manuel Rivas, Trevor Hastie, "A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank." PLoS genetics, 2020.
Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases
Christopher DeBoever, Yosuke Tanigawa, Matthew Aguirre, Greg McInnes, Adam Lavertu, Manuel Rivas, "Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases." The American Journal of Human Genetics, 2020.
Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology
Yosuke Tanigawa, Jiehan Li, Johanne Justesen, Heiko Horn, Matthew Aguirre, Christopher DeBoever, Chris Chang, Balasubramanian Narasimhan, Kasper Lage, Trevor Hastie, et. al., "Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology." Nature Communications, 2019.
Phenome-wide Burden of Copy-Number Variation in the UK Biobank
Matthew Aguirre, Manuel Rivas, James Priest, "Phenome-wide Burden of Copy-Number Variation in the UK Biobank." The American Journal of Human Genetics, 2019.
Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide
Douglas Ruderfer, Colin Walsh, Matthew Aguirre, Yosuke Tanigawa, Jessica Ribeiro, Joseph Franklin, Manuel Rivas, "Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide." Molecular psychiatry, 2019.
Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics
Gregory McInnes, Yosuke Tanigawa, Chris DeBoever, Adam Lavertu, Julia Olivieri, Matthew Aguirre, Manuel Rivas, "Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics." Bioinformatics, 2018.
Landscape of X chromosome inactivation across human tissues
Taru Tukiainen, Alexandra-Chloe Villani, Angela Yen, Manuel Rivas, Jamie Marshall, Rahul Satija, Matt Aguirre, Laura Gauthier, Mark Fleharty, Andrew Kirby, et. al., "Landscape of X chromosome inactivation across human tissues." Nature, 2017.
Presentations
Gene regulatory network structure informs the distribution of perturbation effects
Talk at Genentech, Stanford, CA, USA
Gene regulatory network structure informs the distribution of perturbation effects
Talk at AstraZeneca, Virtual, UK
Gene regulatory network structure informs the distribution of perturbation effects
Talk at Arc Institute, Palo Alto, CA, USA
Gene regulatory network structure informs the distribution of perturbation effects
Talk at Learning on Graphs and Geometry (LoGG) Reading Group, Virtual, USA
Gene regulatory network structure informs the distribution of perturbation effects
Talk at Stanford Department of Biomedical Data Science Festival (DBDSFest), Stanford, CA, USA
Gene regulatory network structure informs the distribution of perturbation effects
Talk at Probabilistic Modeling in Genomics (ProbGen), Vienna BioCenter, Vienna, Austria
Modeling the structure and function of gene regulatory networks: from graph properties to expression variation
Poster at The Biology of Genomes Conference (BoG), Cold Spring Harbor, NY, USA
Simulating effects from genetic and experimental perturbations to gene regulatory networks
Poster at Annual meeting of the American Society of Human Genetics (ASHG), Los Angeles, CA, USA
Modeling quantitative trait locus effects through gene regulatory networks
Chalk Talk at Computational Genomics Summer Institute, University of California Los Angeles, Los Angeles CA, USA
Modeling quantitative trait locus effects through gene regulatory networks
Poster at National Library of Medicine Training Informatics Conference, University of Buffalo, Buffalo NY, USA
Simulating systemic effects of expression quantitative trait loci across gene regulatory networks
Poster at Population, Evolutionary, and Quantitative Genetics Conference, Asilomar Conference Grounds, Pacific Grove CA, USA
Simulating realistic gene regulatory networks and expression data
Talk at Microsoft Research PhD Fellowship Research Showcase, Virtual (Microsoft Research)
A deep learning classifier for local ancestry inference
Poster at National Library of Medicine Training Informatics Conference, Virtual (University of Washington)
A deep learning classifier for local ancestry inference
Poster at Conference on Neural Information Processing Systems (NeurIPS), Virtual
A deep learning classifier for local ancestry inference
Poster at Annual meeting of the American Society of Human Genetics (ASHG), Virtual
Polygenic risk modeling with latent trait-related genetic components
Poster at Annual meeting of the American Society of Human Genetics (ASHG), Houston, Texas
Landscape of genomic copy number variation and effects in UK Biobank
Talk at Statens Serum Institut, Copenhagen, Denmark
Phenome-wide burden of copy number variation in UK Biobank
Talk at 23andme Genome Research Day, Mountain View, CA
Gene-level intolerance to copy number variation in UK Biobank reveals a cohort-level survival bias and novel disease associations
Poster at Annual meeting of the American Society of Human Genetics (ASHG), San Diego, California
Teaching
Service
- Student Representative, Stanford Department of Biomedical Data Science (2022-23)
- Peer Mentor, Stanford Biosciences (2020-2022)
- Research Mentor, Stanford Summer Research Program (SSRP, 2018)