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Peter S. Carbonetto

TitleResearch Assistant Professor
InstitutionUniversity of Chicago
DepartmentHuman Genetics
AddressChicago IL 60637
ORCID ORCID Icon0000-0003-1144-6780 Additional info
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    Collapse Overview 
    Collapse overview
    The main theme of my work is the development of statistical methods and software tools for analyzing genetic data. This work is motivated mainly by advances in genomic technologies for profiling molecules in cells.

    Collapse Biography 
    Collapse education and training
    University of Chicago, Chicago, IL, USApostdoc07/2014Human Genetics
    University of British Columbia, Vancouver, BC, CanadaPh.D.09/2009Computer Science
    University of British Columbia, Vancouver, BC, CanadaM.Sc.09/2003Computer Science
    McGill University, Montreal, QC, CanadaB.Sc.08/2001Computer Science
    Collapse awards and honors
    2010 - 2013Cross-disciplinary Postdoctoral Fellowship, Human Frontiers Science Program

    Collapse Bibliographic 
    Collapse selected publications
    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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    PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. Weine E, Carbonetto P, Stephens M. Accelerated dimensionality reduction of single-cell RNA sequencing data with fastglmpca. bioRxiv. 2024 Mar 27. PMID: 38585920; PMCID: PMC10996495.
      Citations:    
    2. Carbonetto P, Dorkó G, Schmid C, Kück H, de Freitas N. Lecture Notes in Computer Science. A Semi-supervised learning approach to object recognition with spatial integration of local features and segmentation cues. 2024; 4170:285-308. View Publication.
    3. Carbonetto P, Kisynski J, de Freitas N, Poole D. Nonparametric Bayesian logic. 21st Conference on Uncertainty in Artificial Intelligence. 2024; 85-93. View Publication.
    4. Zou Y, Xie D, Carbonetto P, Wang G, Stephens M. Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions. bioRxiv. 2024 Feb 10. PMID: 37425935; PMCID: PMC10327118.
      Citations: 1     
    5. Takahama M, Patil A, Richey G, Cipurko D, Johnson K, Carbonetto P, Plaster M, Pandey S, Cheronis K, Ueda T, Gruenbaum A, Kawamoto T, Stephens M, Chevrier N. A pairwise cytokine code explains the organism-wide response to sepsis. Nat Immunol. 2024 Feb; 25(2):226-239. PMID: 38191855; PMCID: PMC10834370.
      Citations: 2     Fields:    Translation:Animals
    6. Carbonetto P, Luo K, Sarkar A, Hung A, Tayeb K, Pott S, Stephens M. GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership. Genome Biol. 2023 10 19; 24(1):236. PMID: 37858253; PMCID: PMC10588049.
      Citations:    Fields:    
    7. Carbonetto P, Luo K, Sarkar A, Hung A, Tayeb K, Pott S, Stephens M. GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership. bioRxiv. 2023 Sep 14. PMID: 36945441; PMCID: PMC10028846.
      Citations:    
    8. Liu Y, Carbonetto P, Willwerscheid J, Oakes SA, Macleod KF, Stephens M. DISSECTING TUMOR TRANSCRIPTIONAL HETEROGENEITY FROM SINGLE-CELL RNA-SEQ DATA BY GENERALIZED BINARY COVARIANCE DECOMPOSITION. bioRxiv. 2023 Aug 17. PMID: 37645713; PMCID: PMC10462040.
      Citations:    
    9. Morgante F, Carbonetto P, Wang G, Zou Y, Sarkar A, Stephens M. A flexible empirical Bayes approach to multivariate multiple regression, and its improved accuracy in predicting multi-tissue gene expression from genotypes. PLoS Genet. 2023 07; 19(7):e1010539. PMID: 37418505; PMCID: PMC10355440.
      Citations:    Fields:    
    10. Takahama M, Patil A, Johnson K, Cipurko D, Miki Y, Taketomi Y, Carbonetto P, Plaster M, Richey G, Pandey S, Cheronis K, Ueda T, Gruenbaum A, Dudek SM, Stephens M, Murakami M, Chevrier N. Organism-Wide Analysis of Sepsis Reveals Mechanisms of Systemic Inflammation. bioRxiv. 2023 Feb 02. PMID: 36778287; PMCID: PMC9915512.
      Citations:    
    11. Zou Y, Carbonetto P, Wang G, Stephens M. Fine-mapping from summary data with the "Sum of Single Effects" model. PLoS Genet. 2022 07; 18(7):e1010299. PMID: 35853082; PMCID: PMC9337707.
      Citations: 45     Fields:    
    12. Clay SM, Schoettler N, Goldstein AM, Carbonetto P, Dapas M, Altman MC, Rosasco MG, Gern JE, Jackson DJ, Im HK, Stephens M, Nicolae DL, Ober C. Fine-mapping studies distinguish genetic risks for childhood- and adult-onset asthma in the HLA region. Genome Med. 2022 05 24; 14(1):55. PMID: 35606880; PMCID: PMC9128203.
      Citations: 1     Fields:    Translation:HumansCells
    13. Carbonetto P, Sarkar A, Wang Z, Stephens M. Non-negative matrix factorization algorithms greatly improve topic model fits. arXiv. 2022; doi:10.48550/arXiv.2105.13440. View Publication.
    14. Xing Z, Carbonetto P, Stephens M. Flexible Signal Denoising via Flexible Empirical Bayes Shrinkage. J Mach Learn Res. 2021 Jan-Dec; 22. PMID: 38149302; PMCID: PMC10751020.
      Citations:    
    15. Wang G, Sarkar A, Carbonetto P, Stephens M. A simple new approach to variable selection in regression, with application to genetic fine mapping. J R Stat Soc Series B Stat Methodol. 2020 Dec; 82(5):1273-1300. PMID: 37220626; PMCID: PMC10201948.
      Citations: 147     
    16. Kim Y, Carbonetto P, Stephens M, Anitescu M. A Fast Algorithm for Maximum Likelihood Estimation of Mixture Proportions Using Sequential Quadratic Programming. J Comput Graph Stat. 2020; 29(2):261-273. PMID: 33762803; PMCID: PMC7986967.
      Citations: 2     
    17. Blischak JD, Carbonetto P, Stephens M. Creating and sharing reproducible research code the workflowr way. F1000Res. 2019; 8:1749. PMID: 31723427; PMCID: PMC6833990.
      Citations: 22     Fields:    
    18. Urbut SM, Wang G, Carbonetto P, Stephens M. Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions. Nat Genet. 2019 01; 51(1):187-195. PMID: 30478440; PMCID: PMC6309609.
      Citations: 144     Fields:    Translation:Humans
    19. Carbonetto P, Stephens M, Ferrão LFV, Ferrão RG, Ferrão MAG, Fonseca A, Garcia AAF. Accurate genomic prediction of Coffea canephora in multiple environments using whole-genome statistical models. Heredity (Edinb). 2019 03; 122(3):261-275. PMID: 29941997; PMCID: PMC6460747.
      Citations: 13     Fields:    Translation:Animals
    20. Han E, Curtis R E, Carbonetto P. Discovering population structure from patterns of identity-by-descent. 2018. View Publication.
    21. Hernandez Cordero AI, Carbonetto P, Riboni Verri G, Gregory JS, Vandenbergh DJ, P Gyekis J, Blizard DA, Lionikas A. Replication and discovery of musculoskeletal QTLs in LG/J and SM/J advanced intercross lines. Physiol Rep. 2018 02; 6(4). PMID: 29479840; PMCID: PMC6430048.
      Citations: 7     Fields:    Translation:Animals
    22. Carbonetto P, Zhou X, Stephens M. varbvs: fast variable selection for large-scale regression. arXiv. 2017; doi:10.48550/arXiv.1709.06597. View Publication.
    23. Han E, Carbonetto P, Curtis RE, Wang Y, Granka JM, Byrnes J, Noto K, Kermany AR, Myres NM, Barber MJ, Rand KA, Song S, Roman T, Battat E, Elyashiv E, Guturu H, Hong EL, Chahine KG, Ball CA. Clustering of 770,000 genomes reveals post-colonial population structure of North America. Nat Commun. 2017 02 07; 8:14238. PMID: 28169989; PMCID: PMC5309710.
      Citations: 51     Fields:    Translation:Humans
    24. Sittig LJ, Carbonetto P, Engel KA, Krauss KS, Barrios-Camacho CM, Palmer AA. Genetic Background Limits Generalizability of Genotype-Phenotype Relationships. Neuron. 2016 Sep 21; 91(6):1253-1259. PMID: 27618673; PMCID: PMC5033712.
      Citations: 118     Fields:    Translation:Animals
    25. Parker CC, Gopalakrishnan S, Carbonetto P, Gonzales NM, Leung E, Park YJ, Aryee E, Davis J, Blizard DA, Ackert-Bicknell CL, Lionikas A, Pritchard JK, Palmer AA. Genome-wide association study of behavioral, physiological and gene expression traits in outbred CFW mice. Nat Genet. 2016 08; 48(8):919-26. PMID: 27376237; PMCID: PMC4963286.
      Citations: 48     Fields:    Translation:Animals
    26. Sittig LJ, Carbonetto P, Engel KA, Krauss KS, Palmer AA. Integration of genome-wide association and extant brain expression QTL identifies candidate genes influencing prepulse inhibition in inbred F1 mice. Genes Brain Behav. 2016 Feb; 15(2):260-70. PMID: 26482417; PMCID: PMC4873164.
      Citations: 2     Fields:    Translation:Animals
    27. Carbonetto P, Gopalakrishnan S, Parker CC, Ackert-Bicknell CL, Palmer AA, Pallares LF, Tautz D. Mapping of Craniofacial Traits in Outbred Mice Identifies Major Developmental Genes Involved in Shape Determination. PLoS Genet. 2015 Nov; 11(11):e1005607. PMID: 26523602; PMCID: PMC4629907.
      Citations: 37     Fields:    Translation:Animals
    28. Parker CC, Carbonetto P, Sokoloff G, Park YJ, Abney M, Palmer AA. High-resolution genetic mapping of complex traits from a combined analysis of F2 and advanced intercross mice. Genetics. 2014 Sep; 198(1):103-16. PMID: 25236452; PMCID: PMC4174923.
      Citations: 30     Fields:    Translation:AnimalsCells
    29. Carbonetto P, Cheng R, Gyekis JP, Parker CC, Blizard DA, Palmer AA, Lionikas A. Discovery and refinement of muscle weight QTLs in B6 × D2 advanced intercross mice. Physiol Genomics. 2014 Aug 15; 46(16):571-82. PMID: 24963006; PMCID: PMC4137148.
      Citations: 8     Fields:    Translation:AnimalsCells
    30. Carbonetto P, Stephens M. Integrated enrichment analysis of variants and pathways in genome-wide association studies indicates central role for IL-2 signaling genes in type 1 diabetes, and cytokine signaling genes in Crohn's disease. PLoS Genet. 2013; 9(10):e1003770. PMID: 24098138; PMCID: PMC3789883.
      Citations: 35     Fields:    Translation:HumansCells
    31. Zhou X, Carbonetto P, Stephens M. Polygenic modeling with bayesian sparse linear mixed models. PLoS Genet. 2013; 9(2):e1003264. PMID: 23408905; PMCID: PMC3567190.
      Citations: 356     Fields:    Translation:Humans
    32. Carbonetto P, Stephens M. Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies. Bayesian Analysis. 2012; 7:73-108. View Publication.
    33. Carbonetto P, Schmidt M, de Freitas N. An interior-point stochastic approximation method and an L1-regularized delta rule. Advances in Neural Information Processing Systems. 2008; 21:233-240. View Publication.
    34. Carbonetto P, Dorkó G, Schmid C., Kück H, de Freitas N. Learning to recognize objects with little supervision. International Journal of Computer Vision. 2007; 77:219-237. View Publication.
    35. Carbonetto P, de Freitas N. Conditional mean field. Advances in Neural Information Processing Systems. 2006; 19:201-208. View Publication.
    36. Carbonetto P, de Freitas N, Barnard K. A statistical model for general contextual object recognition. 8th European Conference on Computer Vision, Part I. 2004; 350-362. View Publication.
    37. Kück H, Carbonetto P, de Freitas N. A constrained semi-supervised learning approach to data association. 8th European Conference on Computer Vision, Part III. 2004. View Publication.
    38. Carbonetto P, de Freitas N. Why can't José read? the problem of learning semantic associations in a robot environment. HLT-NAACL 2003 Workshop on Learning Word Meaning from Non-Linguistic Data. 2003; 6:54-61. View Publication.
    39. Carbonetto P, de Freitas N, Gustafson P, Thompson N. Bayesian feature weighting for unsupervised learning, with application to object recognition. 9th Workshop on Artificial Intelligence and Statistics. 2003; 124-131. View Publication.
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